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February 3-6, 2016; Milan, Italy; Full Report – Draft

Executive Highlights

This report contains our full coverage of the 9th International Conference on Advanced Technologies & Treatments for Diabetes (ATTD 2016) held in Milan, Italy from February 3-6. This year’s event was the largest ever, bringing over 2,600 delegates from 90 different countries to the Fashion Capital of the World (vs. 2,542 attendees in Paris in 2015). It’s quite something to think how far the field has come since the first ATTD Close Concerns covered in 2009 when we saw exploratory studies of low glucose suspend, sub-group data from the JDRF CGM trial in those with an A1c <7%, and a 12-person study from Abbott’s Dr. Udo Hoss suggesting that Navigator could be factory calibrated (amazing to think how that morphed into FreeStyle Libre five years later). We can hardly wait to see what the field looks like in 12 months when ATTD will celebrate its 10th anniversary in Paris, France from February 15-18, 2017.

1. Abbott’s six-month REPLACE study comparing FreeStyle Libre to SMBG in type 2s with a high baseline A1c (8.8%) disappointingly missed its primary endpoint – similar 0.3% A1c reductions in both groups. The hypoglycemia data, however, was very compelling, showing ~30 minutes fewer per day <70 mg/dl and nearly 10 minutes fewer per day <45 mg/dl. The results serve as a reminder of how much hypoglycemia impacts type 2, how challenging A1c is as a primary endpoint for interventions that reduce hypoglycemia, and the nuances of trial design for diabetes technology. We expect REPLACE will increase the “noise” level on the competitive front overall for Abbott and think it will provide a bit of breather (real or perceived – patients love this device though better data is needed for reimbursement) for Dexcom and Medtronic near term. While the data came well under expectations, Abbott will get very good marks for reducing hypoglycemia at night – and that reduces the noise factor on the absence of alarms.

2. Medtronic had a slew of exciting headlines at ATTD: (i) news that MiniMed 670G US pivotal trial is wrapping up three months ahead of schedule + plans for a 1,000-patient 670G outcomes study; (ii) strong accuracy data on the Enlite 3 and Enlite 4 CGM sensors; (iii) surprise news that the Bluetooth-enabled, standalone Guardian Connect CGM is under CE Mark review; and (iv) plans for new next-gen CareLink reports to optimize pump settings. This company is really moving faster under the leadership of President Hooman Hakami.

3. In CGM, ATTD reinforced that accuracy is necessary but no longer sufficient. With Abbott (FreeStyle Libre), Dexcom (G5), Medtronic (Enlite 3), Senseonics (Eversense), and Roche (Insight) boasting available or upcoming sensors with in-clinic MARDs of ~9-12%, several sensors should be robust enough for dosing insulin. The focus is now shifting to on-body form factor, cost, connectivity, degree of patient burden, provider hassle, and other differentiating factors. The race is on to offer smaller, less expensive, more convenient, and more clinically impactful sensors and software.

5. Artificial pancreas updates included a fascinating debate on the incremental benefit of dual-hormone closed loop; new data from a slew of increasingly long-term trials; and plenty of speculation on the real-world challenges of closing the loop (particularly provider time). Everyone is now counting on Medtronic to launch the MiniMed 670G next year in the US (as of JPM 2016, a launch is expected by April 2017). What is less clear is who will follow Medtronic and how quickly – Tandem? Animas? Insulet? TypeZero? Bigfoot Biomedical? MGH/BU? Others? How big can the market get, what will payers deem meaningful, and what do patients really want (particularly MDI + SMBG users)?

6. ATTD was another reminder that A1c is a profoundly challenging endpoint for diabetes technology. Whether it was Abbott’s REPLACE data (no overall benefit on A1c, but meaningful reductions in hypoglycemia) or the symposium on moving to time-in-range, it’s clear our field must agree on valuable supplements to A1c.

Themes

Abbott’s six-month REPLACE study comparing FreeStyle Libre to SMBG in type 2s with a high baseline A1c (8.8%) disappointingly missed its primary endpoint, showing similar 0.3% A1c reductions in both groups. Based on a pre-specified analysis, A1c did significantly improve with FreeStyle Libre in users <65 years old (-0.5% vs. -0.2%), though it went in the wrong direction in those >65 years old (-0.1% vs. -0.5%). The most compelling takeaway was the hypoglycemia data (measured via masked Libre Pro in the SMBG arm), which improved markedly with FreeStyle Libre overall, overnight, and particularly for dangerous hypoglycemia (<55 mg/dl). Relative to the control group, patients using FreeStyle Libre spent ~30 minutes fewer per day <70 mg/dl (p<0.001), ~13 minutes fewer per day <55 mg/dl (p=0.001), and ~8.5 minutes fewer per day <45 mg/dl (p=0.001). For the FreeStyle Libre group, these reductions equated to major 55%, 68%, and 75% reductions in those respective zones from baseline to six months (based on the limited data given, it was not possible to calculate these percentages for the control group). All measures of nocturnal hypoglycemia were also significantly lower with FreeStyle Libre, countering the criticism that the device’s lack of alarms poses a nighttime danger (presumably, the retrospective glucose data helped identify nocturnal hypoglycemia).

Why did REPLACE miss its primary endpoint? We have a few hypotheses:

The study design did not use a per-protocol mandatory insulin adjustment (i.e., not treat-to-target), which would have unquestionably improved the magnitude of A1c benefit. Providers and patients could decide what to do with the data at their regular visits, a deliberate decision to ensure a real-world trial.

Were providers drawn to the red traffic light on AGP that identifies hypoglycemia – particularly in the older type 2 patients! – backing off therapy accordingly? It is of course much easier to fix hypoglycemia (reduce insulin) than to safely bring mean glucose down (“Is it correction or food bolus? Or is it basal? Or is it...”). This could explain the age difference in the study.

Was this the right study population? These were patients far from A1c goal and already testing four times per day; how much realistic upside was there?

Ultimately, we had very high expectations coming in to REPLACE – it seemed like a slam dunk to improve A1c in insulin-using type 2s (baseline A1c: 8.8%) testing ~four times per day (although, we know that is far more often – 400% more often – than the average type 2). While we were crushed that the trial missed its primary endpoint in all patients, we were pleased to see it showed profound and meaningful reductions in hypoglycemia – particularly the ~75% reduction in time spent at the highly dangerous level <45 mg/dl. The results do serve as a reminder of how much hypoglycemia impacts type 2 and why A1c is the most devilish of outcomes for diabetes technology (as devices typically reduce hypoglycemia at the expense of raising average glucose). It will be interesting to see how the type 1 data from IMPACT (to be shown at ADA 2016) will complement these results; we can only assume similar or larger reductions in hypoglycemia, since patients in that trial have an A1c <7.5%.

We expect these data to increase the “noise” level on the competitive front overall for Abbott, though they will provide a bit of breather (real or perceived – patients love this device) for Dexcom and Medtronic near term. Of course, both Dexcom and Medtronic have some reasons to be worried: Libre’s factory calibration, lower cost, very low-profile form factor, and very quick EU uptake are compelling vs. current CGM. The competition will unquestionably drive faster innovation, and we look forward to what Dexcom does with Verily [Google Life Sciences] and what Medtronic’s type 2 business might deliver.

2. Medtronic – Moving Faster on the 670G, Better CGM, and Software

We left ATTD thinking, “Wow – Medtronic is really moving!” On just about every day of the meeting, there was major Medtronic news left and right: the 670G pivotal study wrapping up three months ahead of time, much improved fourth- and fifth-gen sensors, a standalone Bluetooth-enabled CGM under CE Mark review, and more. The company has really accelerated and broadened under new Group President Hooman Hakami: faster work on its core businesses (type 1 pumps and CGM) plus new work in type 2, apps, and software. Here were Medtronic’s main ATTD happenings:

In a surprise, the US pivotal trial of the MiniMed 670G is “close to the end” – the last patient is expected to leave the study around the end of February, three months earlier than we expected it to end (the ClinicalTrials.gov posting slated completion in May). [Editor’s Note: On March 9, we learned that the pivotal trial had been completed – see our report.] Medtronic expects 100 completers. Dr. Fran Kaufman hinted that the 670G might be available in 2017 with a reference to the US election, “Maybe in the next US President’s first year of office, we can say they live in a country where hybrid closed loop is available.” Medtronic’s latest timeline in its earnings call this week suggested an FDA submission before the end of June, meaning commercialization by April 2017 is still possible (though the FDA review would have to be around 12 months at most). Dr. Kaufman also disclosed that Medtronic is planning a major 1,000-patient post-approval outcomes study of the MiniMed 670G (the biggest study Medtronic Diabetes has ever done). The multinational trial will enroll a representative type 1 population (spectrum of A1cs and ages), randomizing patients to three groups for six months: pump alone, sensor-augmented pump (no automation), or the MiniMed 670G (IF only there was a fourth group on MDI!). The primary endpoint will be glycemic control AND hypoglycemia, with a six-month follow-up period. The study will generate excellent real-world outcomes data, and we especially hope it is powered to show changes in severe hypoglycemia and tracks healthcare costs.

Meanwhile, two Medtronic posters shared more details on the fourth and fifth-generation sensors (i.e., Enlite 3 and Enlite 4).

Accuracy data from a pre-pivotal study of Enlite 3 suggested an MARD of 11% vs. YSI based on two fingerstick calibrations per day (days 1, 3, 7 visits; YSI values recorded every 15 minutes for 12 hours; 4,805 paired points). This sensor will be used with the MiniMed 670G and standalone Guardian Connect mobile app. The accuracy was much stronger on the arm (8.7%) vs. the abdomen (11.9%-12.6%). The seven-day wear Enlite 3 sensor has an improved algorithm with intelligent diagnostics that determine if it is safe to enter closed loop. The algorithm will also request a calibration when the system detects the overall performance can be improved, and data is not displayed when it detects poor sensor performance.

Enlite 4 showed a strong overall MARD of 10.9% vs. the Bayer Contour Next Link meter with one calibration per day and 10-day wear (n=55 sensors, 5,709 evaluation points). We had not ever known this would be 10-day wear or one calibration per day, though that would exactly match Dexcom’s plans for G6. Roughly 45% of sensors had a MARD <10%, with most of the remaining sensors between 10% and 15%. Mean absolute difference (MAD) in hypoglycemia (<70 mg/dl) was 12 mg/dl, and 86% of overall points were within 20 mg/dl or 20%. Some sensors were removed from analysis early due to adhesiveness or battery failures – the percentage was not specified, and both are critical question marks for Medtronic’s clamshell transmitter design (larger on the body and less secure than Dexcom and Abbott sensors). While this is still a feasibility study, this sensor shows a marked improvement from the original Enlite and stands as a signal that Medtronic may be catching up to Abbott and Dexcom’s more accurate sensors.

In an unexpected exhibit hall reveal, Medtronic publicly displayed Guardian Connect, its standalone, Bluetooth-enabled mobile CGM targeted at patients not on pumps. Signs indicated it is currently under CE Mark review. Per Medtronic’s earnings call last week, an EU launch is expected in ~May-July 2016 and an FDA submission will occur in early March. The transmitter is the familiar clamshell design, though it will send CGM data via Bluetooth directly to a mobile app on Apple iOS at launch. Medtronic does not plan to launch a standalone receiver, so patients will only get the transmitter and app. We see this as a key competitive answer to Dexcom’s G5 and Abbott’s LibreLink, plus an important Medtronic foray into MDI (Medtronic’s current real-time CGM requires a paired pump). Though we have known about this device since September 2014 (pivotal study completed in August 2015), this is the first time it has ever been on display in final commercial form in an exhibit hall. See picture below.

Medtronic Diabetes’ Ms. Annette Brüls shared several updates on the company’s software and app plans: (i) confirming the timing from CES to launch a hypoglycemia prediction app with IBM Watson this summer; (ii) sharing new news that the company plans to launch next-gen CareLink Pro reports in the next 12 months (including advanced analytics to optimize pump basal and bolus settings); and (iii) hinting at future plans to build Bluetooth directly into Medtronic’s closed loop (eliminating MiniMed Connect; no timing stated). In the coming months, Medtronic will also launch some of the current CareLink Pro features into CareLink personal, countering longstanding complaints that patients should see the same thing as providers. Ms. Brüls also showed a very compelling example of insightful Big Data (from CareLink) – a colored map of the US compared dangerous hypoglycemia episodes (>3 hours at <50 mg/dl) in patients with threshold suspend turned off vs. on. Patients with threshold suspend turned off experienced 6.1 such episodes per year (!) vs. just 0.8 episodes per patient per year with threshold suspend turned on. The slide suggested the difference (5.3 episodes hypoglycemia) equates to $735 in emergency services per patient per year and $9,300 in patient services per year. Now that is some compelling evidence that even mild automation can make a difference; we can’t wait to see outcomes from the 1,000-patient MiniMed 670G outcomes study.

3. CGM – accuracy is necessary but not sufficient

With Abbott (FreeStyle Libre), Dexcom (G5), Medtronic (Enlite 3), Senseonics (Eversense), and Roche (Insight) boasting available or upcoming sensors with MARDs of ~9-12%, we should have several products robust enough for dosing insulin. The focus is now shifting to on-body form factor, cost, connectivity, degree of patient burden, provider hassle, apps, download software, and other differentiating factors. While there is tremendous room to expand the market, the race is clearly on to offer the smallest, most convenient, easy-to-use, cost-effective, and clinically impactful sensor system (on-body + receiver + app + data management). Dexcom CTO Jorge Valdes shared a few key pipeline updates, highlighting Dexcom’s plans for smaller, connected sensors and predictive algorithms: (i) the new G5 smaller transmitter (expected in late 2016 or early 2017, per JPM) will cut the volume in half vs. the current transmitter; (ii) G5 Android is still expected to launch this year; (iii) Dexcom will incorporate predictive hypoglycemia alerts into G6, offering a larger 15-minute prediction window. Medtronic also had its share of CGM updates at ATTD 2016 (see above), while Abbott announced an expanded indication for FreeStyle Libre in pediatrics (though no new device design updates). Senseonics’ soon-to-launch Eversense implantable CGM sensor showed encouraging data in its EU pivotal study, with an overall MARD of 11.5% vs. YSI at ten in-clinic visits. Roche did not share any specific CGM product updates, but did disclose that studies are progressing, consistent with 4Q15 plans for a 2016 EU launch. What we love about these offerings is their diversity – the competition is driving fast innovation, with a burgeoning number of integration options (phone, pump), user interfaces, data management, and more. We believe that cost and wearing something on the body remain two of the biggest barriers to CGM use, and we wonder who will address those most profoundly going forward. More broadly, how big can the glucose sensor market get as products further improve – what fraction of insulin-using patients will choose to wear a sensor, assuming they get even smaller and less expensive? What will the type 2 and prediabetes markets look like? Will the professional market take off with FreeStyle Libre Pro? Will we see stronger clinical data in CGM, especially showing reductions in healthcare and hospitalizations? Will automated insulin delivery be CGM’s killer app? Will FreeStyle Libre steal significant share from traditional CGM?

4. increasing focus on insulin dose decision support

The challenge of titrating insulin is long recognized, but we’re now finally seeing some real products to tackle this issue – Sanofi’s MyStar Dose Coach meter; DreaMed’s MD-Logic Pump Advisor; Glooko’s type 2 basal insulin titration software (MIDS); Medtronic’s next-gen CareLink reports; and even Tidepool’s Nutshell app. See below for more on each offering. We think these products have the potential to make a difference by providing continual patient support, saving provider time, and (hopefully) improving glucose control. The real-world application question is whether patients and providers will actually use these advances; setup requires time and input on the provider end, and regular use obviously requires patient training and data uploads. If these systems are impactful, however, those should be smaller problems. We wonder how insulin dose decision support systems might be integrated with Bluetooth-connected pumps and BGM/CGM to enable more compelling real-time therapeutic advice, as well as how they might be used in reverse to treat or prevent hypoglycemia (e.g., advising carb consumption based on blood glucose patterns and activity level).

Medtronic plans to launch next-gen CareLink Pro reports in the EU in the next 12 months, which will identify optimal basal and bolus wizard changes, show glycemic trends in a new way, give providers a clinic dashboard, and modify the report design to structure conversation and uncover problem areas. The company will also launch some of the current CareLink Pro features into CareLink personal, countering longstanding complaints that patients should see the same thing as providers.

Sanofi debuted its MyStar DoseCoach BGM in its exhibit hall booth – the meter integrates an insulin glargine dose titration algorithm, providing guidance on insulin dose adjustments for patients with type 2 diabetes. We assume it could conceivably launch soon in Europe (it received a CE mark in December); unfortunately, there is no US timing to report. We hope this system’s convenience and more individualized insulin guidance will bring more patients to goal and save HCPs time.

DreaMed’s exciting MD-Logic Pump Advisor identifies very clear, specific changes in pump settings like basal rates and insulin-to-carb ratio. The initial version will send patient data from the Glooko app to the physician, who will approve the MD Logic Pump Advisor recommendations and send it back to patients. The hope is to eventually send the pump settings recommendations directly to patients without HCP confirmation. The Helmsley Charitable Trust recently awarded $3.4 million to DreaMed to fund the Pump Advisor’s development (leveraging data from the Glooko platform), with a preliminary study starting this fall.

Glooko shared plans to develop two insulin decision support tools: the DreaMed MD Logic pump advisor (see above) and a mobile insulin dosing system (MIDS) that makes it easier for people new to insulin to setup and manage titration calculations for type 2 diabetes. This was the first-ever mention of the latter, which could be very impactful in our view, particularly in the PCP setting. Both systems will help clinicians be more efficient and effective as the software will do analysis and give clinicians and patients crystal clear decision support for changing insulin doses.

Tidepool hopes to release its novel Nutshell app “within the next quarter,” enabling users to improve future mealtime insulin dosing by keeping track of insulin and glycemic data from past meals. We love this idea, since patients tend to eat the same meals, and it makes perfect sense to look at what happened last time and make more informed decisions. Nutshell is currently in beta testing and will be available for free after its launch.

Automated Insulin Delivery (AID) conversation at ATTD included a debate on the incremental benefit of dual-hormone closed loop; new data from a slew of increasingly long-term academic trials, and plenty of speculation on the real-world challenges of closing the loop. There was no major new data from industry, though everyone is now quoting Medtronic’s plan to launch the MiniMed 670G next year in the US (as of JPM 2016, a launch is expected by April 2017). What is less clear is who will follow Medtronic and how quickly – Tandem? Animas? TypeZero? Bigfoot Biomedical? Insulet? MGH/BU? Others? See our updated automated insulin delivery landscape here. There are many questions to answer: How big can the market get and what will patients find compelling from a product design perspective? How should industry think about designing for MDI + SMBG users? What percentage of type 1s are likely to get on AID in the next five years? What about type 2s in the next 10 years? Are payers terrified of AID or excited about the better outcomes? Can AID systems show reductions in hospitalizations and healthcare expenses?

Drs. Steven Russell (MGH, Boston, MA) and Bruce Buckingham (Stanford University, Palo Alto, CA) shared insulin-only data on MGH/BU’s bionic pancreas, which showed roughly similar efficacy in pilot studies to other published systems: an average glucose of ~154-161 mg/dl (depending on the target glucose), with just ~1-3% of the time spent <70 mg/dl. Further, Dr. Russell revealed that the iLet device may be released as an insulin-only product to start – he estimates it could come to market six months to a year before the dual-hormone system. The iLet’s pivotal trial is still expected to start in early 2017, which will include a control arm, an insulin-only arm, and an insulin+glucagon arm.

The single vs. dual hormone debate with Drs. Steven Russell and Tadej Battelino was unquestionably a meeting highlight, endingwith an amicable conclusion: we need both systems. Still, it was clear that this debate won’t be settled until products hit the market – the incremental value of glucagon has to be weighed against the added cost and complexity, which is difficult to unpack in early research studies (these don’t reflect commercial products or real-world populations). It’s clear to us that glucagon adds some benefits over insulin-only systems (less hypoglycemia, lower mean glucose, less user demands to count carbs or announce exercise), though the size of those benefits has to be weighed against the patient tradeoffs that come with a second hormone (larger device, higher cost, more complexity). Dr. Kowalski’s talk put it the best – AID must balance diabetes happiness (quality of life, burden) with diabetes health (A1c, hypoglycemia). Products will clearly fall on a spectrum of those two metrics, and it will be up to patients, providers, and the healthcare system to determine where different products fall and what is worth paying for. We strongly believe the automated insulin delivery field needs a thriving commercial marketplace with multiple systems vying for patients’, providers’, and payers’ attention – that will result in the best personalization of therapy and the fastest iteration to improve on first-gen products.

We also heard from UVA’s Dr. Boris Kovatchev, who shared six-month results from the five-month extension phase of JDRF’s multicenter 24/7 closed-loop trial testing UVA’s DiAs system. The trial’s 14 participants showed sustained and dramatic reductions in hypoglycemia from baseline vs. the last three months of the study – time <70 mg/dl declined ~68% (from 4.1% to 1.3%; p<0.001) and time <50 mg/dl declined a marked ~90% (from 1% to 0.1%; p<0.001). A1c declined a non-significant 0.2% overall at six months from a well-controlled baseline of 7.2% (p=0.16) – a reminder of how non-real-world these AID study populations are.

Another hot topic was the real-world challenges of AID, especially the impact on healthcare providers. The psychosocial artificial pancreas session shared early data from a fascinating new HCP survey (n=370) and patient focus groups (n=60), illustrating some of the key challenges for AID – provider time, reimbursement, varying patient expectations, and the need for serious education. Most notable were the results from the HCP survey, which sampled an early adopter population (370 respondents out of 10,000 invited) that was clearly enthusiastic and comfortable with diabetes technology (e.g., 91% believed that AID will optimize diabetes control in type 1). However, 74% of providers expect to have difficulty getting insurance coverage for AID once it is available, 63% of providers believe that AID will require more professional time than previous approaches to insulin delivery, and 95% believe that educators or trainers will be required to implement and manage AID in patients. The survey reinforced the provider side of this emerging technology – products will need to address limited bandwidth, even in leading clinicians familiar with the technology. It is amazing to see the field thinking about adoption of these systems very broadly; we imagine many are thinking, “Let’s not repeat the slow uptake seen with CGM.” While first-gen CGM products were not ready for prime time, we believe first-gen AID products will be better than many patients are doing on their own.

6. A1c – A profoundly challenging endpoint for diabetes Technology

ATTD 2016 reminded us, yet again, that A1c is a profoundly challenging endpoint for technology that reduces hypoglycemia. Certainly, this was apparent in Abbott’s REPLACE data (no overall benefit on A1c, but meaningful reductions in hypoglycemia), but was just as clear during a Day #2 symposium that focused on how time-in-range can complement A1c. JDRF’s enthusiastic Dr. Aaron Kowalski featured front-and-center in this conversation, emphasizing the need for a metric that captures “value” in diabetes. Of course, value is defined differently for patients, providers, and payers, and Dr. Kowalski noted that the ideal metric will go beyond A1c to include device burden, time investment, fear, provider quality metrics, hospitalizations, etc. – what he called a balance between diabetes happiness (quality of life) and diabetes health (A1c, hypoglycemia). We heard similar comments from Medtronic Diabetes’ Dr. Robert Vigersky and Dr. David Rodbard, who both advocated for “escaping” the A1c-centric world and finding a metric that all stakeholders – regulators, industry, payers, patients, and clinicians – can agree on. Bringing all these parties to the same table remains a barrier and it’s unclear whether the field can agree on a single endpoint (or set of endpoints) to supplement A1c. Everyone seems to agree that time-in-range is a reasonably good starting point, but as Dr. Irl Hirsch pointed out, there is not agreement on the ranges and ideal time spent in those ranges. We like the way Dr. Kowalski put it: the focus should be on improving time-in-range, regardless of what time should be spent there. We have high hopes for JDRF T1D Outcomes Program, which will hopefully meaningfully advance the conversation and carry over into type 2.

1. Automated Insulin Delivery

Debate On Single vs. Dual Hormone Close-Loop

Where Is The Field Right Now?

Aaron Kowalski, PhD (Chief Mission Officer, JDRF, New York, NY)

JDRF’s Dr. Aaron Kowalski delivered big-time enthusiasm on the future of closed-loop work (“We’re on the cusp of a revolution in diabetes care!”), along with balanced views on bihormonal systems (relative to his skepticism in the past). The commentary came in a broader presentation on JDRF’s role in this movement, beginning with the genesis of the JDRF Artificial Pancreas at DTM 2004 through the evolution of current closed-loop systems. The field has come a long way in 12 years – back then, sensors and algorithms were not close to good enough, and smartphones as we know them today did not even exist. In speaking about JDRF’s involvement, he credited former CEO Mr. Jeffrey Brewer (now CEO of Bigfoot Biomedical) for getting the organization’s efforts off the ground, applauding his long-term vision and commitment to catalyzing funding. Dr. Kowalski contrasted current work with some of the earliest artificial pancreas research from Drs. Bill Tamborlane and Stu Weinzeimer at Yale, who began asking questions then (How do we best cover post-prandial spikes? Do we need pre-meal boluses?) that are just as relevant today. As he did earlier in the week, Dr. Kowalski emphasized that closed-loop systems must balance diabetes happiness (quality of life) with diabetes health (A1c, hypoglycemia). Products will clearly fall on a spectrum of those two metrics, and it will be up to patients, providers, and the healthcare system to determine where different products fall and what is worth paying for. This is clearly going to be a JDRF focus area going forward. Overall, this was a valuable and comprehensive presentation that underscored how much JDRF has carried this field; we loved Dr. Kowalski’s optimism and bring you some of his most memorable quotes below (including notable optimism on Afrezza – “The speed of action of Afrezza has been amazing for me!”).

Dr. Kowalski shared big-time enthusiasm for how far the closed-loop field has come, sharing that all six steps of the 2009 JDRF roadmap have been proved in research. He sped through a review of a number of the academic and industry groups working in the field, expressing a great deal of confidence in current efforts. Below is a selection of his praise:

Medtronic: “They are REALLY pushing the field forward.” No question on this – the MiniMed 670G US pivotal study is wrapping up in less than three weeks, and everyone is quoting the expectation for a 2017 launch of this system. Whether Medtronic will meet the April 2017 timeline is an open question.

Bigfoot: “Their initial message was simply that we could do the artificial pancreas. Not sometime in the future; right now.” As he did at ADA 2015, Dr. Kowalski again devoted two slides to a Diabetes Mine guest columnby Sarah Mazlish (Bigfoot), which underscored the reduced “burden” artificial pancreas systems can provide (even to those in very good control like Sarah).

Cambridge: “You saw their publication last year … an amazing amount of work.” [NEJM 2015, in tandem with EASD 2015.]

DreaMed: “Much more safe than what people with diabetes are doing on open loop.” As a reminder, DreaMed licensed its algorithm to Medtronic for systems after the MiniMed 670G; this ATTD it focused on its MD Logic Pump Advisor for optimizing insulin pump settings.

UVA: “They’re in outpatient trials. In kids. In adults. During exercise. This works! It’s safe and effective.”

BU/MGH: “It’s proven. They’ve done outpatient and real-world trials. Dual hormone is very effective. You’ve seen the publications. It works.” This was remarkably positive and refreshing commentary from Dr. Kowalski, who has criticized this system in the past for being dangerous.

“DIYPS?” Dr. Kowalski even pointed out the grassroots, DIY artificial pancreas spearheaded by Dana Lewis, Scott Leibrand, and Ben West. Of course, he cautioned that devices need to be tested and approved, but the #WeAreNotWaiting movement is real – and shows how hungry patients are for innovation. Overall, more than 20 people are using the system globally (we last heard about it at D-Data Exchange last fall), with very positive outcomes. Here’s what Howard Look said about it in a recent tweet on its efficacy: “After one full week on #OpenAPS Avg BG down 30 mg/dL, est A1c down 1.1%, time low down 22% #WeAreNotWaiting.” Though the system is very clunky, it’s efficacy seems to be pretty powerful, even in patients with access to technology.

“The speed of action of Afrezza has been amazing for me!” said Dr. Kowalski.The testament to Afrezza’s real-world efficacy and convenience was striking, echoing what many type 1s have experienced and what MannKind management has shared in calls. Sanofi told us that, nearly two-thirds of users don’t continue using Afrezza after the first prescription, which presumably stems from reimbursement. Dr. Kowalski did not discuss the recent termination of the Sanofi partnership though did acknowledge that the future status of Afrezza is very much up in the air.

Dr. Kowalski also reviewed JDRF’s new T1D Outcomes Program, which aims to define the metrics of importance to people with type 1 diabetes, providers, researchers, industry, FDA, and payers. [We first heard about the program on Day #2 of this meeting.] The assembled steering committee includes all the major professional associations, and we sincerely hope this can move the needle on defining outcomes beyond A1c, and more importantly, getting them accepted.

As always, Dr. Kowalski was one of the more charismatic speakers we get to hear and we bring you some of his most quotable quotes below:

On hacking medical technologies (e.g., DIYPS): “I don’t condone hacking these systems. I want the FDA to approve them. But these grassroots efforts do tell you the incredible need people with diabetes feel for better tools.”

On balancing health and happiness: “There is a balancing act. We have to balance between glycemic outcomes and quality of life. Closed-loop systems are tools that drive benefit on both sides of the equation. That’s where JDRF is going to focus going forward.”

On what the future holds: “We are not successful until all of the steps are done. Research needs to be done. Systems need to be paid for. Indeed, the real metric for this community is people with diabetes doing better.”

Pilot Studies of an Insulin-Only Bionic Pancreas

Bruce Buckingham, MD (Stanford University, Palo Alto, CA)

Dr. Bruce Buckingham presented results from an open-label, non-randomized, pilot study testing an insulin-only version of the bionic pancreas in 13 patients (mean A1c: 7.2%). The outpatient study compared one week of usual care to one week with a fixed glucose target (115-130 mg/dl) to one week with a dynamic glucose target (115-130 mg/dl). From a usual care mean of 145 mg/dl and 5.5% of the time <70 mg/dl (usual care), the insulin-only bionic pancreas raised the mean to 154-159 mg/dl and reduced hypoglycemia by ~50%-66% (1.8%-2.7% time <70 mg/dl). There wasn’t a significant difference between the fixed vs. dynamic glycemic targets. Dr. Buckingham concluded that the insulin only study system “performed similarly to other published insulin-only systems,” and most telling, 12 of the 13 patients said they would take the system home as is. Still, focus groups revealed clear variability in the patient experience: some felt it was “amazing”; some felt it “made them go too high”; many liked not having to carb count; and many experienced Bluetooth connectivity issues with the iPhone driven research platform. As he has in the past, Dr. Buckingham pointed out the discrepancy between patients’ starting baseline A1c (7.2%) and their tighter control during the study’s open-loop phase (approximating an A1c of 6.7%). In comparing six recently published outpatient closed-loop studies (see below), this is actually a consistent finding – from an average A1c at enrollment (7.8%), patients do an estimated ~0.6% A1c points better during the open-loop control phase (7.2%), and a further 0.5% better during closed-loop (6.7%). “Participants in closed-loop studies are not always typical of the type 1 general population – they are often uber users. Once they enter a study, the “control group” glucose levels are often better than would be anticipated by their enrollment A1c.” This has critical implications for assessing the real-world efficacy of closed-loop systems (especially their incremental advantage), and we hope longer randomized pivotal studies can help eliminate this study effect.

This open-label, non-randomized, outpatient pilot study tested an insulin-only version of the bionic pancreas in 13 patients (mean A1c: 7.2%). The study compared one week of usual care to one week with a fixed glucose target (115-130 mg/dl) to one week with a dynamic glucose target (115-130 mg/dl, varying based on risk). In the fixed phase, only one patient used a glucose target of 115 mg/dl; the rest used 130 mg/dl. In all periods, patients were remotely monitored for a glucose <50 mg/dl. The study enrolled 13 participants (nine female) with a mean age of 28, a mean duration of diabetes of 14 years, and a very well controlled mean A1c of 7.2% (ranging from 6.1%-9%).

The insulin only Bionic Pancreas “performed similarly to other published insulin-only systems.” These patients were very well controlled during the usual care phase, so the bionic pancreas mainly helped reduce hypoglycemia.

System

Target BG

Control

Insulin Only

Fixed 115-130 mg/dl

Insulin Only

Dynamic 115-130 mg/dl

Mean

145 mg/dl

159 mg/dl

154 mg/dl

Time <70 mg/dl

5.5%

1.8%

2.7%

Dr. Buckingham noted some of the Bionic Pancreas’ key advantages which are translatable to an insulin-only configuration: (i) it initializes with weight only and without prior insulin or glucose data; (ii) rapid adaption to insulin requirements; and (iii) no carb counting; and (iv) meal adaptation.

Participants in closed-loop studies are not typical of the type 1 general population – they are often über users. Once they enter a study, the “control group” glucose levels are often better than would be anticipated by their enrollment A1c.” Dr. Buckingham showed a slide from the T1D Exchange (see below) highlighting the extremely high A1c’s across the US, particularly in adolescents (the “low-hanging fruit for closing the loop”). It’s abundantly clear that patients in closed-loop studies are doing far, far better on their own open-loop therapy than most with type 1 diabetes.

Study

Type

Enrollment A1c

Control estimated A1c

Closed-loop estimated A1c

Russell Lancet DM 2016

Bihormonal

7.8%

7.4%

6.4%

Russell NEJM 2014

Bihormonal

8.2%

7.1%

6.6%

Russell NEJM 2014

Bihormonal

7.1%

7.2%

6.3%

Ly Diabetes Care 2015

Insulin-only MiniMed 670G

8.6%

6.7%

7.1%

Leelaranthna Diabetes Care 2014

Insulin-only MPC

7.6%

7.1%

6.7%

Thabit NEJM 2015

Insulin-only MPC

7.6%

7.5% (7.6%)

7.1% (7.3)

Average

7.8%

7.2%

6.7%

Insulin-Only Systems Are The Way To Go

Dr. Tadej Battelino opened the debate with a strong case against glucagon, concluding that the added benefit of the hormone is limited and comes at the price of higher cost, greater inconvenience, and increased patient burden. To emphasize the small incremental utility of glucagon in decreasing hypoglycemia, Dr. Battelino highlighted data from Cambridge’s NEJM 2015 paper demonstrating the very low rate of hypoglycemia in closed loop insulin delivery (2.9% in adults and 3.1% in adolescents) compared to sensor-augmented pump therapy (3.0% in adults and 3.8% in adolescents). He also argued that glucagon is ineffective in hyperinsulinemia, citing data showing that moderate doses of subcutaneous glucagon are insufficient at high insulin levels (>40 mU/L) – of course, such levels are rarely achieved with hybrid closed loop, but it is important to note that glucagon won’t always work. To further illustrate his point, Dr. Battelino presented results from the Bionic Pancreas NEJM 2014 bihormonal closed loop study showing that the need for “rescue carbohydrates” to treat hypoglycemia was not completely abolished in the Bionic Pancreas arm, despite the low percentage of time spent below 70 mg/dl (4.8%) in this group. There was also no significant difference in glycemic variability between the Bionic Pancreas arm and control. Dr. Battelino also provided a direct comparison between Cambridge’s NEJM 2015 paper (single hormone) and the Bionic Pancreas NEJM 2014 paper (dual hormone), highlighting that the Cambridge insulin-only system attained a lower percentage of time below 70 mg/dl compared to the Bionic pancreas (2.9% vs. 4.1% in adults). These insights were thought-provoking, but the cross-study comparison was extremely difficult to interpret – the two studies’ design, settings, and participant profiles were very different, making it challenging to draw reliable conclusions about the research platform systems. However, Dr. Battelino’s perspective was another reminder that the value of glucagon is still controversial, and there is a need for more comparative studies of single vs. dual-hormone systems – particularly commercial-ready devices.

To address the relative efficacy of single vs. dual hormone systems, Dr. Battelino provided a direct comparison between Cambridge’s NEJM 2015 paper and the Bionic Pancreas NEJM 2014 paper. This reiterated Dr. Roman Hovorka’s commentary from ADA 2015 and DTM 2014 on a similar comparison. Dr. Battelino highlighted that the Cambridge insulin-only system attained a lower percentage of time <70 mg/dl compared to the Bionic pancreas (2.9% vs. 4.1% in adults). He did acknowledge, however, that the dual hormone system achieved greater time in range of 70-180 mg/dl compared to the insulin-only (80% vs. 68% in adults). He expressed concern for the high dose of glucagon administered by the dual hormone system, as well as the hypoglycemia risk if the glucagon infusion fails. While we find this perspective provocative, the studies are of course very different, making it difficult to draw reliable conclusions about the comparative value of the two closed loop systems.

Dr. Battelino raised additional issues inherent to glucagon use, including increased risk of nausea and vomiting and the potential for higher alcohol intake to compromise its effect. He also noted that elevated glucagon itself can have a detrimental effect on the body by producing hyperinsulinemic hypoglycemia and diabetes – though we would point out that neither of this are much of a concern in people with diabetes.

Dual Hormone Is The Way To Go

Steven Russell, MD, PhD (MGH, Boston, MA)

Dr. Steven Russell provided convincing arguments supporting bihormonal closed-loop, but for the first time, shared that the Bionic Pancreas may be approved and launched as an insulin-only system – with glucagon to be added later. Though we’ve known since last year that the Bionic Pancreas pivotal trial will include an insulin-only arm, this was the first mention at a conference of a potential two-phase commercial pathway. The pivotal trial is still expected in early 2017, consistent with the DTM 2015 timing.Dr. Russell said an insulin-only system could come out “six months to a year earlier,” and the team would launch the iLet dual chamber integrated pump with the glucagon chamber closed off; when a stable glucagon is eventually approved, people could choose to add glucagon if they wanted. The biggest gating factor in the team’s plans still seems to be a stable glucagon, and for the first time, Dr. Russell shared enthusiasm for Zealand’s liquid glucagon analog (completed phase 1 studies), in addition to Xeris’ phase 2 candidate. Previously, Xeris was always the front-runner, though we sensed more enthusiasm for Zealand in this talk. Complementing Dr. Bruce Buckingham’s presentation, Dr. Russell also shared new insulin-only data on the bionic pancreas from head-to-head work at MGH/BU. Overall, subtracting glucagon is not hurting the system in early results – at a glycemic target of 130 mg/dl, the insulin-only bionic pancreas achieved a mean glucose of 161 mg/dl with 0.8% time <60 mg/dl. By comparison, the bihormonal setup achieved a similar average of 156 mg/dl and 0.5% time <60 mg/dl (target 130 mg/dl). When the target was lowered to 100 mg/dl with the bihormonal system, the average improved significantly without adding hypoglycemia: 136 mg/dl and 0.8% time <60 mg/dl. Thus far, the team has only tested 145 and 130 mg/dl targets for insulin-only, and we wonder how it will do at 115 and 100 mg/dl. Overall, we’re glad to see MGH/BU doing these comparative studies, which are critical for documenting the incremental glycemic benefits of glucagon. That said, Medtronic could launch the MiniMed 670G next year before the Bionic Pancreas pivotal trial is even over; how might an insulin-only Bionic Pancreas stack up against the 670G? How much will glucagon add (lower mean glucose, less hypoglycemia, lower user demands) relative to its drawbacks (higher costs, larger device, more complexity)? It’s hard to answer these questions without final commercial devices, patient preference information, and longer-term data. We hope many systems come to market, giving patients and providers more options to personalize therapy.

Dr. Russell shared head-to-head data from an ongoing study comparing insulin-only and bihormonal versions of the bionic pancreas at different glycemic targets.“Glucagon allows a lower mean without increasing hypoglycemia.” This data complemented the results from insulin-only work at Stanford, presented by Dr. Bruce Buckingham earlier in the session. It’s clear that the Bionic Pancreas works in insulin-only mode, though the added advantage of glucagon is hard to assess at this stage – rates of hypoglycemia are so low in all cases (0-1.4%) that the numbers are not real world. We assume as the team tests a lower insulin-only set point (115 or 100 mg/dl), the difference in hypoglycemia will become much clearer – at 130 mg/dl, the two configurations are nearly identical, clinically speaking.

System

Target BG

Control

Insulin Only

145 mg/dl

Insulin Only

130 mg/dl

Bihormonal

130 mg/dl

Bihormonal

115 mg/dl

Bihormonal

100 mg/dl

Mean

158 mg/dl

174 mg/dl

161 mg/dl

156 mg/dl

146 mg/dl

136 mg/dl

Time <60 mg/dl

1.4%

1.0%

0.8%

0.5%

0.9%

0.8%

“You can only compare two systems within a study.” Dr. Russell countered Dr. Battelino’s exploratory head-to-head comparison between the Bionic Pancreas (NEJM 2014) and Cambridge (NEJM 2015). First, both trials had different study designs and different patient populations. He most the different study environments and levels of activity, particularly when the Bionic Pancreas was tested in the diabetes camp (“a very, very tough environment to do studies in”).

More broadly, he noted that the two artificial pancreas systems ask different things of the user. Insulin-only systems (such as Dr. Hovorka’s) require carb counting and users to calculate boluses. The bionic pancreas only asks for a qualitative estimate of meal size (Is this the amount you typically eat, smaller, or larger?), and users are not required to announce meals. In the NEJM studies, users bolused for ~70% of meals, leaving the system fully automated for the remaining ~30%.

Dr. Russell was balanced throughout his talk: “I would not support the proposition that dual hormone is only way to go. There are two options, and both have clear benefits, as Dr. Kowalski mentioned. Clearly, insulin-only can provide better control that usual care in diabetes. There is no doubt that they provide benefit. But I want to argue that glucagon can provide incremental, additional benefit over insulin-only systems.”

Dr. Russell shared many convincing arguments in favor of using glucagon:

Even the normal pancreas uses glucagon to control blood glucose, and it has ideal insulin pharmacokinetics (no peripheral delays, short time to peak). In people without diabetes, glucagon levels are normally increased in settings of threatened hypoglycemia and exercise.

Type 1 diabetes includes a functional glucagon deficiency. The alpha cells, in the absence of beta cell products (insulin or zinc are candidates for the missing factor), lose the ability to regulate glucagon in type 1 diabetes. Without a glucagon response, the only choice for people with type 1 is to withhold insulin or take carbs.

The need for insulin can decrease faster than insulin can be withdrawn. Dr. Russell gave a hypothetical to illustrate the point: with a blood glucose at 100, imagine needing to run for the bus, causing a fall in glucose of 2 mg/dl per minute. That leaves just 15 minutes until someone hits 70 mg/dl. With a seven-minute lag time for CGM, that further leaves just eight minutes that the system actually knows glucose is falling. Suspending insulin with a seven-minute head start won’t prevent someone from going low. The only solution with an insulin-only system, therefore, is to warn the user they are going low and tell them to take carbs.

Glucagon allows more spontaneity of the user (no need for carbs). See example above. Glucagon is absorbed quickly, taking just 20 minutes to peak and beginning to work within five minutes. It can very quickly prevent hypoglycemia that might have otherwise occurred.

Glucagon allows the artificial pancreas system to ask less of the user (alarms, carbs, meal announcements). As a reminder, the bionic pancreas does not require meal announcement, as previous studies suggest it does nearly as well.

A dual hormone pump is needed. Dr. Russell showed a picture of the dual-chamber iLet device, first unveiled at FFL 2015. The Bionic Pancreas team has developed the fully integrated pump, which will be used in the expected 2017 pivotal trial and submitted to FDA. Who will manufacture the pump is an unknown.

A second hormone adds cost. Dr. Russell admitted there will be a cost increase, though he believes it “will be modest and justified.” In his view, the incremental cost of adding another pump drive train is “not much” compared to a total pump’s cost. In terms of paying for an additional hormone, he said, “We’ll have to see if insurers, providers, and patients think that the additional glucose lowering, lower risk of hypoglycemia, and spontaneity are worth it. I would argue it will be, but we’ll have to see how it goes.” We thought this was a remarkably fair and honest characterization.

There is no stable glucagon available. Dr. Russell actually believes two stable glucagons will be ready for clinical trials in 2017: Xeris and Zealand. Though we’ve long known about the team’s plans to use Xeris’ glucagon, the mention of Zealand came for the first time. Dr. Russell noted that Xeris’ glucagon is more stable than Zealand’s glucagon analog, but Xeris’ use of the additive DSMO would require specialized infusion set plastics (the iLet system has been built with this in mind). Zealand’s glucagon has stability suitable for pump use (not quite as stable as Xeris, as it must be refrigerated until use), and Dr. Russell believes it could last in a pump for six days.

Zealand has completed several phase 1 studies with its stable glucagon analog, but has moved quickly to prioritize it in the past year and has more resources than Xeris. Xeris is prioritizing its rescue pen for severe hypoglycemia (shorter time to market), though that has taken much longer than initially expected.

Glucagon increases insulin use and hides faults of the insulin algorithm. In fact, the team’s 11-day multicenter outpatient study demonstrated nearly identical insulin use in usual care vs. the bihormonal bionic pancreas: 0.66 u/kg vs. 0.63 u/kg. The average total daily dose of glucagon was 0.51 mg. The same was true of the team’s camp study in pre-adolescents, just published in Lancet Diabetes and Endocrinology (first shared at CMHC 2014): 0.68 u/kg vs. 0.66 u/kg. In these settings, the Bionic Pancreas is using the same amount of insulin, lowering mean glucose, and reducing hypoglycemia.

An insulin-only bionic pancreas works well already. To this criticism, Dr. Russell only pointed out, “If your algorithm is tuned with insulin only, wouldn’t you further reduce hypoglycemia by adding glucagon?”

Glucagon adds risks – what if it fails? If glucagon is not available for any reason (occlusion, empty reservoir, etc.), the Bionic Pancreas will default to a higher set point in an insulin-only configuration. The team has also built a custom snakebite infusion set with two rigid steel cannulas – it will be impossible to pull out only one catheter. Last, steel cannulas cannot kink, adding further safety (we’d note that this set is not commonly used in the US, so it will be interesting to hear how patients like it). “Even if something happened that we could not mitigate,” said Dr. Russell, “we’re probably going to do better than usual care.”

Glucagon causes nausea. Dr. Russell mentioned the team’s glucagon only home use study, presented at AADE 2015. In the randomized, placebo controlled, double blind trial, participants wore a pump with either glucagon or placebo every day while regulating their own insulin. They were selected for hypoglycemia unawareness. Glucagon reduced hypoglycemia by 74%, and there was no difference in reported nausea. In addition, the trial’s blinding was totally effective: patients correctly guessed they were on glucagon vs. placebo on only 42% of days (less than chance!). There were no adverse events associated with glucagon. Said Dr. Russell, “We couldn’t have been causing too many side effects, since they didn’t know they were getting glucagon.” A compelling point!

Glucagon will deplete liver glycogen. There was no evidence of this in the team’s 11-day multi-center study. Dr. Russell also mentioned work from the OHSU team (Castle et al., Diabetes Care 2015), which showed that repeated doses of glucagon do not lead to any detriment in rise of blood glucose. The study also used imaging to assess glycogen in the liver, confirming that glucagon works in fed and fasted states. The amount of glycogen in the liver, said Dr. Russell, can take much more glucagon than the bionic pancreas gives.

Chronic glucagon might be unsafe. In the 11-day multi-center study, there were no concerns about weight, blood pressure, or any safety signals (including complete hematology and chemistry panels) with use of the bionic pancreas. Second, people with hyperglucagonemia have levels that far exceed average levels with the bionic pancreas, and tumors that secrete glucagon are often discovered incidentally (without symptoms). Of course, this argument may not be fully settled until the pivotal trial is completed, which is designed for a chronic use indication for glucagon.

Panel Discussion

Dr. Aaron Kowalski: Can we get to a place where we can compare best in class insulin-alone to best in class insulin and glucagon? In an apples-to-apples comparison? How do we get to that point?

Dr. Russell: I think it’s hard to do that kind of comparison, even if you put the two systems in the same context. For instance, our system requires less of the user by design and doesn’t require carb counting. That adds some quality of life, which we have been very focused on. We tested our system, and with no meal announcements, it works well – lack of meal announcements only raises mean glucose by 13 mg/dl. We tell people meal announcements are recommended but optional. If we did a best in class test and had meal announcements optional, would the proponents of insulin-only systems agree to that trial design? It is hard to directly compare in an apples-to-apples format. I would be very interested to use an insulin-only controller, add glucagon to it, and see what incremental benefit there could be. If the insulin controller is really well designed, more hypoglycemia should be prevented with glucagon.

Dr. Battelino: Wise people once said that “better is the enemy of good.” Patients said, “Come on with the closed loop.” Single hormone closed-loop seems to be extremely safe, physical, and very close to the patient. This is what we should do because this is what we owe them. If we discover a better option, then we can use that. One person tweeted what if we have faster insulin? We do. It’s coming. The whole paradigm is shifting. My suggestion is let’s reunite and deliver a closed-loop to our patients that is safe and effective, and I yes I will be extremely eager to improve.

Dr. Russell: I agree we should deliver both or more – 2-4 systems. I don’t think there’s any evidence that using the dual hormone will delay things much. We are planning a true pivotal trial in early 2017. The trial is a little longer, and the data will be used for an indication for chronic use of glucagon. We will add an insulin-only arm to the trial. We think we might be able to get our insulin-only system out six months to a year earlier while we are waiting for the glucagon indication. The plan is to release the system with the glucagon chamber closed off, and people can add glucagon when we get approval.

Brandon Arbiter (Tidepool, San Francisco, CA): I’ve been fortunate to live on an artificial pancreas – first the DiAs system and now a homemade system (DIYPS) – for the past 6-7 weeks. It is unbelievable to wake up at 100 every day. The ironic part is I wake up at 100 and feel so good that I want to go for a run and I can’t believe I have so much insulin on board (IOB). At that moment, having glucagon would be great. The last thing you want to do before you exercise is eat something – it’s depressing. The concept of daily use glucagon is so interesting, and we don’t have that at all today. Are there potential form factors other than pumping for daily use of glucagon? Locemia’s nasal glucagon is just for severe hypoglycemia rescue.

Dr. Russell: Both Xeris and Zealand say they are working on multi-dose pens so you can use low dose glucagon whenever you want.

Dr. Battelino: There are also patches in development.

Dr. Russell: The Bionic pancreas will let you do a G-burst, to give a small dose of glucagon on demand. It is primarily for if you decide that you’re going to disconnect for a while and are close to the bottom of the normal range. For example, if you’re going to take a shower you might give 100 micrograms of glucagon to bump you up so you don’t have to take a snack.

Dr. Garry Steil (Boston Children’s Hospital): What is the instance of hypoglycemia in a normal, glucose tolerant child? Do they ever have BGs below 60? Do we see hypoglycemia in a normal healthy person?

Dr. Buckingham: When we were first studying with DirectNet, we wanted to see how sensors worked. You have sensor data and there’s always a question whether the sensor failed and is reading a false low or if it is a real low. We also brought them into the CRC. There were a few occasions when kids were in the 60s on YSI overnight. This was in the controls without diabetes.

Dr. Steil: Do we have an over-perception of the risk of danger of hypoglycemia in the presence of low insulin? Clearly that’s very different than the presence of hypoglycemia at high insulin.

Dr. Battelino: Can a European pediatrician respond? Yes, we fear hypoglycemia too much.

Dr. Russell: The reason we fear mild hypoglycemia is the concern that it could be a harbinger of more severe hypoglycemia. We have increasing levels of concern associated with 70’s, 60’s, 50’s, 40’s, etc. Below 60’s we start to get worried.

Dr. Saleh Adi (UCSF): I have a question for Dr. Kowalski. This is all very exciting and obviously it’s coming. In 2017, hopefully we will have more than one system. Every patient is going to have one. My concern is are we preparing the field enough for these new devices and new systems to come? Are we training our healthcare workforce to be ready for this? We need to understand before we give our patients these devices to use. How will we troubleshoot when something goes wrong? Who is going to tweak the algorithm? Will I need to hire a software engineer in my practice? This is what makes me nervous. What is JDRF doing to prepare us for that?

Dr. Kowalski: This is probably the most important point in this field right now. I’ve been on CGM for ten years, but if you look globally, there are many barriers to CGM use such as cost and clinical adoption. When I question glucagon, the complexity becomes an extra barrier. We need data. In terms of conditioning of the market – we haven’t succeeded until that happens. This is a huge focus for JDRF, Helmsley Charitable Trust, and the T1D Exchange, and we are launching a multi-million dollar policy initiative for it.

Q: What we really care about are episodes of severe hypoglycemia. What we see in almost all these trials is that patients with severe hypoglycemia are being excluded. Can we get data on patients who need it most? Do we think the indication for dual hormone will be for people with a higher risk for severe hypoglycemia?

Dr. Russell: We need bigger trials to get data on severe hypoglycemia. Trials so far have been too small to get data on that. We don’t exclude patients for severe hypoglycemia unless they had a seizure in the past six months.

Adam Brown (Close Concerns, San Francisco, CA): Can we get to a point where we test best-in-class systems head to head? Let’s put MiniMed 670G against the iLet. Let’s track healthcare costs and outcomes and what patients and providers actually prefer. Let’s allow people to choose and we can see. Drug companies test different drugs against each other all the time. Why can’t we do the same with devices?

Dr. Battelino: If you want a trial to see whether Mercedes or BMW is better it will be hard. But I see no harm in seeing how a couple of excellent systems compare.

Artificial Pancreas Psychosocial Measures Project

Introduction

Richard Bergenstal

Dr. Richard Bergenstal’s succinct opening introduction posed a couple of important and impactful questions for the session:Will the artificial pancreas help us reach the triple aim? Will it bring value to type 1 diabetes care? “If there’s only one word to emphasize,” he said, “it’s value. That’s outcomes/cost.” It’s the bar any device or drug must meet, but an especially challenging one to define for automated insulin delivery, given the slew of non-clinical benefits (peace of mind, burden, stress, worry, etc.). As Dr. Bergenstal challenged in Q&A, quantifying those aspects – and bringing them to payers in a compelling way – is not easy. Still, the team working on this project clearly has that end goal in mind, and we’re encouraged to see the progress thus far through both qualitative and quantitative research.

Data From Healthcare Professional Survey

Kellee Miller, PhD (Jaeb Center for Health Research, Tampa, FL)

Dr. Kellee Miller shared early results from a valuable HCP survey, which sampled an early adopter population (370 respondents thus far out of 10,000 invited) that was clearly enthusiastic and comfortable with diabetes technology (e.g., 91% believe AID will optimize diabetes control in type 1). A notable 66% of providers reported that they currently have difficulty getting insurance coverage for CGM in type 1s (only 33% for pumps), and the stat was equally concerning for automated insulin delivery: 74% of providers expect to have difficulty getting insurance coverage for AID once it is available. Also alarming (though to be expected) were perceptions about the time investment automated insulin delivery will require. A sound 63% of providers believe that AID will require more professional time than previous approaches to insulin delivery, and 95% believe that educators or trainers will be required to implement and manage AID in patients. Interestingly, there was a pretty even provider split on perceptions of patient cost-sharing: 39% of providers think patients will be willing to share the cost of AID with insurers and payers vs. 21% that were neutral vs. 41% that don’t think patients will share costs. A notable 33% of providers – and these were individuals clearly comfortable with technology – said they will wait to prescribe AID until there is sufficient long-term evidence of success with the technology. Last, only 47% of providers trust AID systems to perform at the highest level of accuracy and precision. There were a slew of other questions on AID, pumps, and CGM, but overall, this survey reinforced the provider side of automated insulin delivery – there are serious concerns about reimbursement and time, even in leading clinicians familiar with the technology. We can’t imagine what the results would look like for PCPs.

Data From Qualitatie Phase

Katharine Barnard, PhD (University of Southampton, UK)

In a bullet-point style presentation, Dr. Katharine Barnard listed the key themes about automated insulin delivery (AID) that have emerged following 60 focus groups of people with type 1 and their caregivers (n=26 adults with type 1; 11 youth/teens with type 1; 15 parents; and 8 partners). Ultimately, data from the HCP survey (above), patient focus groups, and previous evidence will be used to build five age-based measures to quantify the psychosocial impact of AID in type 1 diabetes. The goal is to help regulatory approval bodies, payers, HCPs, and patients effectively assess the psychosocial impact of this technology. Notably, the FDA is actively engaged with the program, and the team plans to meet with them on February 19. Once complete, the measures will be piloted in clinical research studies testing AID systems. As Dr. Aaron Kowalski pointed out in Q&A, this is about moving the conversation beyond A1c, and certainly, AID has a lot of benefits beyond glycemic control. We salute the Helmsley Charitable Trust for funding this valuable program and for researchers for working on it so diligently, in such forward-thinking, patient-friendly, value-oriented ways.

There is an overwhelming expectation that AID help manage diabetes. But what are the different levels of automation? (e.g., carb counting, levels of bolusing). Partners and children and teens had less understanding of AID systems than adults.

There is also confusion around the namesartificial pancreas vs. closed loop and if they mean the same or different thing. This will be key once products come to market and for setting clear expectations. There is definitely a need to come up with uniform terminology.

Views on AID as a “cure” also differ. User input and visibility/wearing a device prevent AID from being a “cure.” Some believe that significant minimization of user input would be a cure, while others want to a see significant improvement in glycemic control. It should be acknowledged that even the word cure is in the eye of the beholder!

Hopes/Expectations for AID: reduced mental burden; improved glycemic control; fewer highs/lows and reduced variability; reduced risk of long-term complications; better quality of life due to less diabetes-related stress; less user input = less chance for human error; similar experience to current tech (pumps, CGM) – though MDI users are less enthusiastic about wearing devices; device aesthetics: sleek, modern, color choice; control from smartphone to aid discreet bolusing.

Potential downsides/barriers: Want more evidence that it works; becoming complacent or dependent on the system; forgetting how to perform routine diabetes tasks (similar to how patients forget how to do injections when their pump fails); concerns if insurance stops funding it; stigma associated with the visibility of devices; too many alarms; pain of cannula insertions (CGM, pump); system failure (what is the backup?); CGM inaccuracy; incorrect dosing of insulin; limited real estate on body of children for cannulas.

When is AID most useful? All the time; at night; mealtimes; exercise; when busy such as during work or school; when stressed; for travel or camp. People clearly want to use the technology for different things. We believe “in real life” the simplicity and ease of use will be key – we think patients will find the value at night to be significant, since there are so many fewer barriers to AID working well (no meals or exercise interruptions) and that although it’s important in the day, the value will be perceived as less by many early on since meals and exercise and stress will prevent most forms of AID from working as well as they will at night. Experiences will vary, of course.

Factors that would impede trust in AID: Letting go control of diabetes after self-management for decades; prior negative experience with pumps or CGM. We would add early adopters who are used to “running things” and have a hard time ceding control may also be patients who feel less trust.

Relationship impact of AID: Positive – improved sleep for loved ones; decreased stress and improved quality of life for partners; avoid arguments about blood sugar numbers; less worry, think/talk about other things than diabetes; reduce tension between adolescents and parents and between parents. Negative – using system during intimacy.

Financing an AID system: Some (not all) would be willing to pay more if necessary. Youth may expect their parents to make sacrifices to pay for the system. Parents would be willing to pay more than currently. Partners would pay anything to make sure their partner received the technology. Most hoped/expected insurance companies to pay and hoped premiums would not increase. Some (not all), adults hoped health utility of the device (reduced long term complications) would motivate insurers to pay.

Plenary: Closing The Loop

Longer Term Closed Loop Use During Free Living Home Settings

Roman Hovorka, PhD (University of Cambridge, UK)

Dr. Roman Hovorka shared an updated overview of Cambridge’s upcoming pre-pivotal studies (three longer-term trials using Medtronic devices!) and hinted at rethinking the team’s clinical study design around easier comparators (vs. their typical sensor augmented pump – we’d love to see different comparators, since the SAP is so far from standard of care). On the pre-pivotal front, Dr. Hovorka laid out a slew of ambitious trials slated for the near future – some of which we had heard of before and some of which we hadn’t: (i) a 3-month, 24/7 closed-loop RCT in adults and children piloting the team’s new setup (Medtronic’s MiniMed 640G/Enlite 3 + an Android phone running Cambridge’s MPC); (ii) a 12-month RCT in children and adolescents [n=130; 6-18 years; 24/7 closed loop (n=65) vs. sensor-augmented pump (n=65); primary endpoint = A1c]; and (iii) a 24-month RCT in newly diagnosed children/adolescents with type 1 diabetes. What is unclear is whether the Cambridge group will use data from these studies to support a regulatory submission. We don’t believe so judging from previous commentary upon receiving an NIH grant– “facilitate pivotal studies” – suggesting that a pivotal study to support PMA application is still in the works. This group, though, continues to put together multicenter trials that are very scientifically rigorous and we salute their work in really blazing a trail of ambitious, at-home, free-living closed-loop studies. Dr. Hovorka did not comment on the team’s commercialization plans.

“I fully agree that one needs to think about study design and reimbursement. We are tempted to rethink what we have done in the past.” Dr. Hovorka spoke to the importance of thinking critically about comparator groups in closed-loop studies, noting that the ultimate goal is to allow the maximum the number of people to benefit from the technology. The Cambridge team has ambitiously and unfailingly used sensor-augmented pump therapy as the comparator (harder than MDI, the best alternative therapy available), though the trade-off, of course, has been diminished contrast between the intervention and control groups. From an academic perspective, we can certainly see how SAP as the control group makes the most sense since studies are scientifically testing whether the addition of a closed-loop algorithm to SAP makes a difference. At the same time, practical considerations would seem to advocate for a more real-world approach – after all, to get the penetration everyone is hoping for, AP studies need to expand beyond sensor-augmented pump users alone and enroll a broad spectrum of type 1s, including those on MDI/SMBG and pumps alone. It’s notable to hear Dr. Hovorka reconsidering this design and we heartily salute his opened-minded, patient-centric approach. We hope pivotal studies and outcomes studies enroll a broad spectrum of type 1s. Automated insulin delivery should appeal to more than just current pump+CGM users – the market will be too small otherwise.

JDRF Multi-Center 6-Month Trial Of 24/7 Closed-Loop Control

Boris Kovatchev, PhD (University of Virginia, Charlottesville, VA)

Dr. Boris Kovatchev shared six-month results from the five-month extension phase of JDRF’s multicenter 24/7 closed-loop trial testing UVA’s DiAs system (we saw one-month results at ADA 2015). Overall, 14 participants were recruited to use DiAs in the five-month extension phase, with sustained and dramatic reductions in hypoglycemia from baseline vs. the last three months of the study – time <70 mg/dl declined ~68% (from 4.1% to 1.3%; p<0.001) and time <50 mg/dl declined a marked ~90% (from 1% to 0.1%; p<0.001). A1c declined a non-significant 0.2% overall at six months from a well-controlled baseline of 7.2% (p=0.16); however, A1c was significantly reduced in three out of four sites (-0.5%, -0.4%, and -0.2%; p=0.02), with one site seeing a converse 0.5% increase in A1c (presumably due to the reduction in hypoglycemia). Extension participants spent an impressive 77% of the time in 70-180 mg/dl overall, with 83% time-in-range at night – DiAs really shines while patients are sleeping (it steadily targets 120 mg/dl by morning), and we expect many well-controlled patients will get a lot of benefit from only using it at night. As has been demonstrated with CGM data, outcomes were related to system use – those who wore DiAs >70% of the time experienced an outstanding 87% reduction in time <70 mg/dl (from 7% to 0.9%; p=0.01) and a 0.5% reduction in A1c (baseline: 7.2%; p=0.02). We see this as terrific efficacy in very well-controlled patients. Overall, DiAs was used in closed-loop mode about 70% of the time during the extension, encouraging utilization for a 24/7 system still in the research phase (participants had to carry an Android smartphone, Accu-Chek pump, and G4 Share receiver). The team is gearing up for the International Diabetes Closed Loop trial (n=240), which will generate the safety and efficacy data to satisfy a regulatory submission after six months. As a reminder, this trial will use a commercial version of DiAs from startup TypeZero (see our previous report). Dr. Kovatchev did not mention the partnership with Cellnovo for this trial (announced during ATTD; see below).

Dr. Kovatchev shared a striking testimonial from the extension phase, a clear statement of how much automated insulin delivery will help many with type 1: “When the study started my A1c was 7.7%, half way through it had dropped to 7.1%, and on the morning before we turned in the equipment, I had my regular, quarterly appointment with my endocrinologist and my A1c was.....drum roll please ..... 6.6. Is that awesome or what?!?! That is my all-time lowest A1c ever! Along with the drop in my A1c, I have lost 22 pounds...”

For the first time, Dr. Kovatchev revealed that the International Diabetes Closed Loop trial (n=240) will have both hypoglycemia and A1c outcomes, depending on baseline characteristics. For those with an A1c >8%, the team aims to see reduction in A1c without increasing hypoglycemia. For those below 8%, the team wants to see the reverse – a significant reduction in hypoglycemia without an increase in A1c. We like the approach!

Phase 1 of the trial (one month long) was presented at ADA 2015 and demonstrated: The primary endpoint of hypoglycemia (time spent <70 mg/dl) was halved overall (4% during open loop vs. ~2% during closed loop; p<0.05), with a marked improvement at night (improved by more than two-thirds, 3% to ~0-1%; p<0.05). Overall 24-hour time-in-range (70-180 mg/dl) improved a bit (66% in open-loop vs. ~73% in the two closed-loop phases of the study), as did overnight time-in-range (62% to ~71-74%).

You can read Adam and Kelly’s personal experience in phase 1 of this study here – they found that the overnight algorithm was excellent (it treated to a target of 120 mg/dl by 7 AM), and the daytime algorithm erred on the side of conservative in this feasibility study. They both loved the overnight system and were glad to see the daytime version being tested to identify and work out bugs.

Looking ahead, Dr. Basu at the Mayo Clinic is notably NIH-funded to test a triple-hormone artificial pancreas system (insulin+glucagon+amylin). The slide indicated a timeline of 2015-2020, so we’re not sure when the study will actually begin. The goal, of course, is to replace the three missing hormones in type 1 diabetes –this is exciting from a full automation perspective, though cost and real world usability are key concerns. UVA’s Dr. Marc Breton is also NIH-funded (2015-2019) to test a multi-signal artificial pancreas system to deal with exercise (informed by a body sensor array: blood glucose, heart rate, physical activity).

Industry Updates

Cellnovo Partners With TypeZero

In an unexpected announcement, Cellnovo announced a partnership with TypeZero to use its patch pump system in the upcoming NIH-funded International Diabetes Closed Loop Trial (n=240), starting in 2H16. The trial will use multiple pump brands (2+), and others will be announced soon. The goal is for patients in this trial and other upcoming studies to have the option of choosing which pump they want to use – we love that. We’d assume Tandem and Insulet are the most likely other pumps to be chosen for these studies. As a reminder, this trial will test a commercial version of UVA’s DiAs system (TypeZero’s inControl AP) paired with a Dexcom CGM; it is intended to support a PMA submission, and FDA has informed the trial design (see our previous coverage). The announcement did have some contradictory wording – the subtitle firmly states trial will use the pump, while the first paragraph says “in consideration for use.” The latter reflects a hedge on the regulatory front (IDE approval is always uncertain, particularly for Cellnovo’s currently EU-only pump), and of course, the fact that other pumps will be used in the trial too. The algorithm integration path is still under consideration – TypeZero may integrate the algorithm into Cellnovo’s handset or keep it in a smartphone platform. The selection of Cellnovo is sensible from a design perspective, as its connected handheld offers remote monitoring and a better user interface than most traditional pumps. Additionally, one-third of IDCL sites are in Europe, where Cellnovo’s pump is already approved. The announcement is a definite victory for Cellnovo, who is still in the early stages of commercializing its pump (224 systems shipped since launching in 2014). The company has a seen a marked decline in valuation since its IPO last July (down to ~€53 million from ~€83 million in 3Q15 and ~€139 million shortly following the IPO), and we’ve heard about some key management departures in recent months. Still, we’re encouraged to see TypeZero enabling patient choice, as usability is such a major part of closing the loop successfully.

Ahmad Haidar, MSc (Ecole Polytechnique de Montreal, Quebec, Canada)

Ahmad Haidar presented a small (n=23) 60-hour randomized trial comparing sensor-augmented pump therapy (SAP) vs. insulin-only closed-loop vs. insulin+glucagon closed-loop. Glucagon showed a small hypoglycemia benefit and no advantage on time-in-range. The outpatient study used a Roche pump, Dexcom CGM, and had patients carb count and meal bolus. Mr. Haidar skipped over the rest of the study design details too quickly to even take a picture of. Results showed a marginal benefit for glucagon in hypoglycemia: time <72 mg/dl was 7.9% with SAP vs. 3.9% with insulin-only closed loop vs. 3.6% with insulin+glucagon closed-loop (p=0.07 for single vs. dual-hormone). The advantage was bigger for time spent <63 mg/dl, where hypoglycemia was halved with glucagon: 3.5% vs. 1.9% vs. 0.9% (p<0.05 for single vs. dual-hormone). Surprisingly, there was no significant difference between the interventions on mean blood glucose (135 mg/dl vs. 142 mg/dl vs. 142 mg/dl). Time-in-range was also not significantly different between any of the interventions, though it trended better with more automation (64% vs. 75% vs. 79%). The Montreal team uses the same insulin algorithm during single- and dual-hormone, meaning it does not dose more aggressively with glucagon. We’ll be interested to see what results look like tomorrow from the insulin-only tests of the Bionic Pancreas! We are fans of more options for patients, and believe dual-hormone could be worth it for those desiring full automation or at serious risk of hypoglycemia. Of course, the additional cost and complexity has to be weighed against any potential clinical advantages.

A Novel Metric Capturing the Therapeutic Value of a Predictive Artificial Pancreas Algorithm

Daniel Finan, PhD (Animas Corporation, West Chester, PA)

Animas engineer Dr. Daniel Finan introduced the Artificial Pancreas Activity Event (APAE) metric as a new concept to help capture the therapeutic value of artificial pancreas devices. He opened his presentation by emphasizing that the emergence of commercial AP devices necessitates new tools for data analysis, specifically pointing to the need of metrics that are simple and meaningful for the user. Dr. Finan thus highlighted that the APAE may fill this gap – he explained the metric’s two analogous versions: (i) the APAE-Hypo (which occurs when the algorithm reduces insulin significantly to mitigate/avoid a hypoglycemic excursion); and (ii) the APAE-Hyper (which occurs when the algorithm increases insulin significantly to mitigate/avoid a hyperglycemic excursion). According to Dr. Finan, this metric will help capture instances when the algorithm has successfully averted situations in which the patient would have been alarmed, instilling the patient’s confidence in the system – an important benefit for anyone relinquishing control of insulin to a semi-automated system. In addition, Dr. Finan noted that the APAE’s guided analysis can also help patients and providers fine-tune the patient’s pump settings. There was no discussion of plans to implement this metric in any devices. As of Day #1, Animas is currently planning its next study of the Hypo-Hyper minimizer system with the FDA. [Editor’s Note: On March 1, Animas contacted us to share that this study IS in fact a pivotal study! This was not evident in Dr. Finan’s remarks in Q&A on Day #1. More details here.]

Greater Freedom with Advanced Technology

Dr. Fran Kaufman gave a masterful overview of Medtronic’s efforts to close the loop, sharing that the US pivotal trial of the MiniMed 670G is “close to the end” – the last patient will leave the study in just 25 days, three months earlier than we expected it to end (the ClinicalTrials.gov posting slated completion in May). [Editor’s Note: On March 9, we learned that the pivotal trial had been completed – see our report.] Medtronic expects 100 completers. Dr. Kaufman hinted that the 670G might be available in 2017 with a reference to the US election, “Maybe in the next US President’s first year of office, we can say they live in a country where hybrid closed loop is available.” That reinforces the confirmations to date that the 670G will be available by April 2017. Indeed, as a reminder, Medtronic’s latest JPM timeline suggested commercialization by April 31, 2017, and given the early pivotal study conclusion, that timeline seems imminently more possible, though the FDA review would have to be around 12 months at most. Dr. Kaufman also disclosed that Medtronic is planning a major 1,000-patient post-approval outcomes study of the MiniMed 670G (the biggest study Medtronic Diabetes has ever done). The multinational trial will enroll a representative type 1 population (spectrum of A1cs and ages), randomizing patients to three groups for six months: pump alone, sensor-augmented pump (no automation), or the MiniMed 670G (IF only there was a fourth group on MDI!). The primary endpoint will be glycemic control AND hypoglycemia, with a six-month follow-up period. The study will generate excellent real-world outcomes data, and we especially hope it is powered to show changes in severe hypoglycemia and tracks healthcare costs.

As Medtronic disclosed at DTM, Dr. Kaufman mentioned that some 670G trial participants have successfully petitioned the FDA for continued access and use of the system. She shared a striking quote from one letter for the first time, a testament to the enthusiastic patient reaction: “Dear FDA: I am currently participating in a 3-month home study of the Medtronic 670G insulin pump. This pump has changed my life and that of my whole family immensely.” We see this as a positive early sign of a system people want to use – “I don’t want to give it back” – and we’re glad to see Medtronic and the FDA making this possible. Apart from the benefit for these patients, it also suggests FDA has become more confident in the real-world safety of closed loop systems. That might result in a speedier review, though it’s always hard to predict.

We’ll be interested to see what the three-month pivotal trial outcomes look like – what kind of time-in-range, A1c improvements, and reductions in hypoglycemia should be expected? We’d note that the pivotal study is single-arm and will only have 100 completers, so it won’t be ideal for comparing the system’s efficacy to other interventions. We believe Medtronic opted for the fastest, most efficient study to get the 670G to market, and the larger post-approval outcomes study will generate the comparative efficacy data everyone is keen to see.

Dr. Kaufman showed a schematic to explain how the MiniMed 670G algorithm works, the most detailed we’ve ever seen. It begins with patient specific parameter estimation and daily adaptation. At the start of hybrid closed loop, there is a sensor accuracy check, along with a glycemic target adjustment for a smooth transition to closed-loop. The 670G will revert to open loop if the sensor is inaccurate. Medtronic is using an ePID controller, which has “normal mode” and “exercise mode.” Dr. Kaufman mentioned targets of 120 and 150 mg/dl, respectively, though it was not clear if these are set or can be adjusted. The device has a max insulin limit, and it will switch to safe mode or the pre-programmed basal rate in cases like sensor failure.

At this point, a remarkable 21 investigator initiated studies (including eight 670G studies) have inform the design of the MiniMed 670G system. Dr. Kaufman admitted that the company has not been as aggressive in publishing data on the system. The system has been stressed with exercise, unannounced meals, sensor failure calibrations, lost transmission, maximal insulin delivery, and in pediatrics. This put into perspective the resource challenges other companies are probably facing – building a closed-loop device is seriously expensive and time consuming.

Dr. Kaufman showed an automated insulin delivery landscape slide, listing competitors with Medtronic’s next-gen DreaMed system in the following order: Bigfoot, University of Cambridge, University of Virginia/TypeZero, Boston University, and Animas. The slide specified the algorithm types (proprietary, MPC) and listed all as 24-hour systems; there was no timing attached to any product. This was a unique gesture we have not ever seen in a closed-loop presentation, and it was interesting that Medtronic views these systems as competitors to its next-gen system after the 670G – though the 670G will come to market earlier than these systems, we had assumed at least some of these competitors could launch a year or two later. The slide was missing Tandem and Insulet, who also have active artificial pancreas programs. See our latest competitive landscape here.

As of November 2015, Medtronic estimates five artificial pancreas systems are in “early development”, five are pre-clinical, 22 are in clinical trials, one is in the approval process (the 670G), and one is “inactive” (we’re not sure who that refers to). The slide said this combines “looking online, gathering data, and trying to understand the landscape.” It is certainly far more systems than we are aware of from the traditional players, but perhaps it is counting academic closed-loop systems.

Further Integrating Care Together

Annette Brüls (VP and President, Diabetes Service and Solutions, Medtronic)

In a most valuable talk, Ms. Annette Brüls confirmed the timing from CES to launch a hypoglycemia prediction app with IBM Watson this summer. In new news, she shared plans to launch next-gen CareLink Pro reports in the next 12 months (including advanced analytics to optimize pump basal and bolus settings), along with future plans to build Bluetooth directly into Medtronic’s hybrid closed loop (eliminating MiniMed Connect; no timing stated). In the coming months, Medtronic will also launch some of the current CareLink Pro features into CareLink personal, countering longstanding complaints that patients should see the same thing as providers. It is great to see the company responding to this feedback. Throughout her talk, Ms. Brüls emphasized the “journey outside of devices” and towards “holistic solutions” that use real-time data from personal Medtronic devices, the Internet of Things, and Big Data to reduce the burden of diabetes. Of course, all these things intertwine, as Ms. Brüls showed in a compelling example of insightful Big Data (from CareLink). A colored map of the US compared dangerous hypoglycemia episodes (>3 hours at <50 mg/dl) in patients with threshold suspend turned off vs. on. Patients with threshold suspend turned off experienced 6.1 such episodes per year vs. just 0.8 episodes per patient per year with threshold suspend turned on. The slide suggested the difference (5.3 episodes hypoglycemia) equates to $735 in emergency services per patient per year and $9,300 in patient services per year. This is the most valuable kind of analysis, which should persuade payers of the value of technology in the real-world. The company’s investment in connectivity, apps, and digital health was crystal clear after this talk, and it’s remarkable to reflect on how different Medtronic Diabetes is from a few years ago – we wouldn’t have thought it was possible.

The next-gen CareLink provider reports launching in the EU in the next 12 months will identify optimal basal and bolus wizard changes, show glycemic trends in a new way, give providers a clinic dashboard, and modify the report design to structure conversation and uncover problem areas. The pump settings optimization is something that HCT just funded DreaMed to build, and it’s impressive that Medtronic is already ready to launch this.

Ms. Brüls was clearly excited about the IBM partnership and suggested that future apps could predict hyperglycemia or show glycemic profiles around specific meals – e.g., helping identify patients’ best meals or worst meals, giving recommendation in a particular situation based on previous behavior, or suggesting what happened in similar patients.

A compelling colored map of the US compared dangerous hypoglycemia episodes (>3 hours at <50 mg/dl) in patients with threshold suspend turned off vs. on. Patients with threshold suspend turned off experienced 6.1 such episodes per year vs. just 0.8 episodes per patient per year with threshold suspend turned on. The slide suggested the difference (5.3 episodes hypoglycemia) equates to $735 in emergency services per patient per year and $9,300 in patient services per year. We love this sort of analysis, which we hope can persuade payers of the value of technology in the real-world.

Shahram Ebadollahi, PhD (Chief Science Officer, IBM Watson Health)

Following Mr. Brüls introduction, IBM Watson Health’s Chief Science Officer Dr. Shahram Ebadollahi gave an outstanding, most valuable presentation on the growth of unstructured data, the company’s plans with Watson, and new data on the Medtronic hypoglycemia prediction app from an analysis of 2,000 users’ CareLink data. The early results from DTM are still holding, showing 80-85% hypoglycemia prediction accuracy three to four hours ahead of time.

Dr. Ebadollahi shared a new analysis from the development of the Medtronic hypoglycemia prediction app – this time with 2,000 users’ CareLink data (the DTM analysis was in 100 users). Watson analyzed data from MiniMed 530G and CareLink users with three to nine months of pump and CGM data. Watson takes into account long-term behavior (pump settings, frequency of excursions in the last month), short-term trends (current trend, sensor glucose, current carb size, bolus size), and demographic features (age, time since diagnosed, time on insulin) to figure out what is most indicative for prediction of hypoglycemia. Data was split into 80%-20% train-test ratio (80% historical patient data, more than three to nine months old) was used to train the classifier).

Watson analyzed the data, identified 10 clusters of patients, and developed specific hypoglycemia prediction models for each of them. An example of three of the clusters of patients: (i) young patients, early onset age, <5 years on insulin; (ii) early 30s, early onset (<10 years), >19 years on insulin; (iii) elderly, late onset, and long-term insulin users (>20 years).

“The goal is to get to an n of 1. Can we get to a prediction machine for every single patient?” Dr. Ebadollahi emphasized the importance of having group-specific prediction models, which are much more accurate than blanket prediction models for the whole population. It is hugely impressive that Watson can do this just by learning from the data.

Watson demonstrated 80%- 85% hypoglycemia prediction accuracy three hours ahead of time, and a remarkable 79-83% accuracy with a four-hour prediction window. The slide listed the prediction accuracy for all ten groups, and the lowest on the slide was an impressive 78.6%.

A list of IBM Watson partners notably excluded Novo Nordisk, who announced a partnership with the group in December. The slide included Medtronic Diabetes, CVS Health (adherence), J&J (orthopedics), Teva (real world evidence), Under Armor (exercise), and Apple HealthKit and Research Kit.

Unstructured data is growing exponentially and projected to reach 44 zettabytes by the year 2020: we learned from Dr. Ebadollahi if grain of rice is a byte, a zettabyte will fill up the Pacific Ocean – that means 44 zettabytes is 44 pacific oceans. Dr. Ebadollahi emphasized that growing data volume and complexity demands a new approach. Structured data was the previous generation of data, though the predominant new types of data are unstructured: sensors and devices, medical images, images/multimedia, natural language, enterprise data. Every five years, he said, the available knowledge in medicine doubles.

A vast amount of untapped data could have a great impact on our health – yet it exists outside medical systems. As evidence, Dr. Ebadollahi pointed to an oft-quoted study that health is comprised of 10% clinical factors (0.4 TB per lifetime), 30% genetics (6 terabytes of data per lifetime), and 60% exogenous factors (1000 terabytes per lifetime).

​SmartGuard: Let The Minimed 640G Do The Work

Pratik Choudhary, MD (King’s College Hospital, London, UK)

Dr. Pratik Choudhary shared new real world data from 4,818 EU users of Medtronic’s MiniMed 640G/Enlite Enhanced system with SmartGuard. Based on data collected from CareLink personal uploads (this is a remarkably valuable dataset), SmartGuard performed remarkably well over the yearlong study period – in 693,623 total SmartGuard events, 75% occurred without sensor glucose levels ever reaching the pre-set low limit (3.6 mmol/l, 65 mg/dl on average). Further, the mean sensor glucose value at suspend was 5.2 mmol/l (94 mg/dl), glucose returned to a normal range within two hours in 90% of SmartGuard events, and users spent ~70% time “in range” – between 3.9 and 10 mmol/l (70-180 mg/dl). The number was not compared to baseline, so it’s hard to know if this was an improvement; we assume it was. Notably, the Enlite Enhanced sensor had a MARD of 11.9% in this study, suggesting improved accuracy over the original Enlite (MARD of 13-14%). While the system achieved impressive hypoglycemia prevention, it did not appear to increase glycemic variability, and insulin delivery auto-restarted to prevent rebound hyperglycemia in two-thirds of SmartGuard events. Dr. Choudhary repeatedly emphasized that SmartGuard resulted in less rebound hyperglycemia compared to low glucose suspend systems. Dr. Choudhary repeatedly highlighted the provider and patient learning curve with the 640G – the challenge is learning to trust the system and not take action when it suspends in the target range to prevent a low. In a workshop earlier in the week, he highlighted that the team now turns off the predicted low alarm, as the 640G takes care of lows in background better than users do when the alarms go off.

Dr. Choudhary shared data collected from CareLink personal uploads from 4,818 EU patients using Medtronic’s MiniMed 640G/Enlite Enhanced system with SmartGuard. Patient ages ranged from 0 to 56+, with the greatest number under the age of 15. Perhaps the earliest adopters of the 640G have been younger patients, or perhaps parents of children with diabetes are far more likely to upload to CareLink than adults with diabetes.

Users spent an impressive ~70% time “in range” – between 3.9 and 10 mmol/l (70-180 mg/dl), and <2% of the time ≤ 2.7 mmol/l (50 mg/dl). The proportion of time spent between 2.8 and 3.9 mmol/l (50-70 mg/dl) and ≥ 16.7 mmol/l (300 mg/dl) was also low (~4% and ~7%, respectively). Average time spent in the 10-16.6 mmol/l (180-300) range was larger at ~30% of a 24-hour period. The number was not compared to a baseline value; we assume it did improve, but are not sure of the magnitude. We love moving toward this kind of analysis that goes so far beyond A1c.

The SmartGuard system perform particularly well at night, with sensor glucose levels reaching the pre-set low limit in only 24% of events. By comparison, 26% 0f SmartGuard events that occurred during the day reached the pre-set low glucose limits. This is excellent real-world efficacy in our view – three out of four times, SmartGuard completely avoids a low.

Dr. Choudhary also shared results from a within patient comparison of patients who switched from Veo to the 640G (n=851), demonstrating that patients had 0.26 less hypoglycemic events per day when using SmartGuard. Notably, this occurred without a coinciding increase in hyperglycemia.

Mr. Choudhary positioned these results as corroborating those from the 40-patient user evaluation study that we reported on at last year’s ATTD, though we would point out some subtle differences: the real-world MARD was higher than that demonstrated by the user evaluation (11.9% vs. 9.8%), and the percentage of SmartGuard events that reached the low limited was substantially higher than we wrote last year (25% vs. 3%). However, it is tough to compare the two given the very different sample sizes (40 vs. almost 5,000 participants), and the study biases inherent to the user evaluation study (patients knew they were being studied and possibly performed better as a result) did not exist for this very real world data analysis.

In terms of future data analysis, we would be curious about how users’ A1cs may have changed during the study period (did A1c increase as a result of reduced hypoglycemia?), as well as how the SmartGuard system might affect behavior – does a behavioral response to predicted low glucose (consuming carbohydrates) combined with a system response (shutting off insulin) cause rebound hyperglycemia?

Corporate Symposium: Animas Academy – A New Educational Resource For People With Diabetes and Healthcare Professionals​ Hypoglycemia-Hyperglycemia Minimizer (Supported by Animas)

Daniel Finan, PhD (Animas Corporation, Westchester, PA)

Animas algorithm scientist Dr. Daniel Finan delivered a dry background presentation on the artificial pancreas, finally revealing in Q&A that Animas is currently planning its next study of the Hypo-Hyper minimizer system with the FDA. [Editor’s Note: On March 1, Animas contacted us to reveal that it will indeed be a pivotal study (!), which was not evident in Dr. Finan’s remarks. More details here.] Animas now considers “off-platform or ancillary software” as part of the artificial pancreas system, suggesting it may incorporate some kind of mobile app or remote monitoring system into the HHM. At least five minutes were devoted to Dr. Aaron Kowalski’s six-step artificial pancreas roadmap, which is now outdated as of his Diabetes Care update last summer. Dr. Finan placed Animas’ HHM as the precursor to a hybrid closed loop (e.g., Medtronic’s MiniMed 670G), suggesting it may not be as aggressive or burden alleviating as the 670G. Overall, the relatively pace of Animas’ automated insulin delivery program has been disappointing but we hope people remember the commercial realities of diabetes devices and the SMBG market. As background, of course, the JDRF partnership was signed in January 2010, with the expectation it would be submitted to FDA within four years. We were all a bit more hopeful back then about timing. There’s no question Animas will be later to market than Medtronic’s MiniMed 670G (pivotal study ending soon; expected to launch by April 2017 in the US); see our latest competitive landscape here.

What is Animas Academy?

Katharine Barnard, PhD (University of Southampton, UK)

Psychologist Dr. Katharine Barnard introduced Animas Academy, a new educational website with practical pump therapy tips for patients, caregivers, and healthcare providers. The website has launched in the UK, with further European countries coming. Animas has done a good job of making the content holistic (everything from basal rates to exercise to sleepovers), layering the content within five broad chapters (Get started with your pump, pump therapy essentials, day to day life, for your kids, HCPs), and refining the content down to key bullet points. The exercise section Dr. Barnard showed had a short summary at the top, “need to know” bullet points, “Do” and “Don’t” bullet points, FAQs, a short training video, and a quiz. The esteemed Dr. Barnard repeatedly emphasized that everything is evidence-based. There is also an HCP section of the website, which includes a virtual pump tour and downloadable PDF guides. Dr. Ralph Ziegler followed Dr. Barnard and walked through the CME-facing portion of Animas Academy, which revolves around four patient case studies and is highly interactive via a live voting system. Overall, Animas has clearly put a major investment in this educational program, and we salute the company for making the content comprehensive (not just about the pump), clear to navigate, and boiled down to key takeaways. We wonder how many patients, caregivers, and providers will actually use it – many pump and diabetes education programs already exist, though significant educational gaps still exist. What is most preventing patients from maximizing pump therapy – is it lack of education, challenges with the products, the difficult of dosing insulin, the food environment, etc.? We’re going to try to track down the very busy Dr. Barnard and get her worldview on some of these questions.

2. Glucose Monitoring

Oral Presentations

Use of Novel Flash Glucose-Sensing Technology to Optimize Glucose Control in Individuals with Type 2 Diabetes on Intensive Insulin Therapy (REPLACE)

Thomas Haak, MD (Diabetes Center Mergentheim, Germany)

Dr. Thomas Haak shared long-awaited results from Abbott’s FreeStyle Libre REPLACE study, a randomized six-month trial comparing Abbott’s new flash glucose monitoring (the FreeStyle Abbott Libre) to SMBG in type 2 patients on basal/bolus therapy in poor control (baseline A1c: 8.8%) on insulin therapy. The session was jam packed (they stopped letting people in), and we have all the data and Close Concerns’ own analysis below. Patients were 2:1 randomized to either use capillary blood glucose testing (n=75; FreeStyle Lite ~ 4 times per day) or real-time use of FreeStyle Libre (n=149) for self-management and review at regular clinician visits. The trial’s primary outcome was not met at six months – from a baseline of 8.8%, both the SMBG and FreeStyle Libre groups experienced a 0.3% reduction in A1c (p=0.82). A pre-specified secondary analysis did reveal an A1c advantage in the subgroup <65 years old: -0.5% vs. -0.2% (p=0.03). The opposite was true in patients ≥65 years, who actually performed far better in the control group (-0.1% vs. -0.5%; p=0.008), which we believe was probably due to HCP caution over having these patients “too” well controlled and risking hypoglycemia.

Overall, the most compelling takeaway from this trial was the hypoglycemia data (measured via masked Libre Pro in the SMBG arm) improved markedly with FreeStyle Libre overall, overnight, and particularly for dangerous hypoglycemia. Had hypoglycemia been the primary outcome, the trial would presumably easily have been a success. Relative to the control group, patients using FreeStyle Libre spent ~30 minutes fewer per day <70 mg/dl (p<0.001), ~13 minutes fewer per day <55 mg/dl (p=0.001), and ~8.5 minutes fewer per day <45 mg/dl (p=0.001) – remarkably strong in our view, especially since any time spent at 45-55 mg/dl is very dangerous and can easily result in an ambulance call or hospital visit or stay. For the FreeStyle Libre group, these reductions equated to major 55%, 68%, and 75% reductions in those respective zones from baseline to six months (based on the limited data given, it was not possible to calculate these percentages for the control group). All measures of nocturnal hypoglycemia were also significantly lower with FreeStyle Libre,countering the criticism that the device’s lack of alarms poses a nighttime danger - presumably, the retrospective glucose data helped identify nocturnal hypoglycemia. There were no device-related serious adverse events and nine instances of minimal adverse events (e.g., infection, allergy) from six subjects.

Ultimately, we had high expectations coming in to this trial – it seemed like slam dunk to improve A1c in insulin-using type 2s (baseline A1c: 8.8%) testing ~ four times per day though we note those are highly engaged patients (the average person with type 2 tests less than once a day and plenty even on mealtime insulin test less). We are extremely disappointed that the trial missed its primary endpoint in all patients. That said, it showed profound and meaningful reductions in hypoglycemia – particularly the ~75% reduction in time spent <45 mg/dl – and patients <65 years did see a 0.3% benefit on A1c while simultaneously reducing severe hypoglycemia – a clear win! A1c is the most devilish of outcomes for diabetes technology, as devices typically profoundly reduce hypoglycemia, often at the expense of raising average glucose.

We do wonder what could have been done differently. Most importantly, the study design did not use a per-protocol mandatory insulin adjustment (i.e., not treat-to-target), which would have unquestionably, in our view (and other smart people) improved the magnitude of A1c benefit. In this trial, providers and patients could decide what to do with the data at their regular visits, a deliberate decision to ensure a real-world trial – that said, it’s been clear for some time that if people do not take action on data, A1c will not improve! We wonder if providers were drawn to the red traffic light on AGP that identifies hypoglycemia – particularly in the older type 2 patients! – and backed off therapy as a result (and too much?). Of course, it is also much easier to fix hypoglycemia (reduce insulin) than to safely bring mean glucose down (“Is it correction or food bolus? Or is it basal?”)

We also wonder about the study population, as these were patients far from A1c goal and already testing four times per day. Within that framework, the full results have to be interpreted in the proper context – not a smashing success and not a success in terms of primary outcome, but clearly a major success in terms of safety. Notably, this trial could have met its primary endpoint with a hypothetical 0.5% reduction in A1c for all patients, and could’ve reduced hypoglycemia at the same – that would have been a clear success but we still consider this directionally very strong, as we think with the right advice from doctors or nurses, patients will be able to drop their A1c.

All things considered, we salute Abbott for conducting this ambitious, long-term outcomes study of FreeStyle Libre. The ultimate mark of any technology is whether patients will buy it, and with FreeStyle Libre, they are paying out of pocket and demanding it faster than Abbott can make sensors. In the immortal words of highly regarded Dr. Jane Seley, whom we saw during ATTD, “and patients will do this – they WANT this!” Of course, reimbursement will open access for far more patients, and we hope this study and subsequent studies make a strong case that more frequent, actionable glucose data is beneficial. An A1c impact will make things more clear – this is also a reminder that A1c is isolation just isn’t the best metric – and we question why hypoglycemia wasn’t included as a primary outcome. Last, it will be extremely important to see how the type 1 data from IMPACT (to be shown at ADA 2016) will impact these results – since we know that patients acting on data can reduce A1c and make for “higher quality” A1cs, we hope we see that. Since patients in that trial have an A1c <7.5%, there may well be room for an even bigger impact on the hypoglycemia front.

Study Design

REPLACE (ClinicalTrials.gov Identifier: NCT02082184) randomly assigned 224 type 2 patients on insulin therapy to six months of either capillary blood glucose testing (n=75; FreeStyle Lite) or sensor glucose data (n=149; FreeStyle Libre) for optimization of glucose levels. All patients entered the study as regular blood glucose testers (≥10 fingersticks/week, averaging to roughly four per day). During the study phase, patients in the intervention arm reviewed FreeStyle Libre Software summary reports (Ambulatory Glucose Profiles) with their clinician at regular intervals in order to make therapy adjustments, while those in the control arm reviewed diary readings with their clinician at similar intervals.

Notably, insulin dose adjustments were made on an intention-to-treat basis. Providers were instructed to optimize therapy as they saw fit, but there were no A1c targets or previously mandated dose adjustments.

Patients at baseline had a mean age of 59 years, a mean 17 year duration of diabetes, a mean A1c of 8.8%, a mean BMI of 33 kg/m2, and a mean self-reported blood glucose frequency of ~3.7 per day. Roughly 95% of patients (n=212) were on MDI. In short, this was a challenging population in which to show benefit (not at goal but testing four times per day), but also one with high potential to reduce A1c meaningfully if they were acting on data.

Results

Use of FreeStyle Libre was associated with significantly improved A1c in subjects <65 years but not for the entire population. Mean A1c improvement in the total population was a similar 0.3% for both groups (p=0.82), who started with baseline A1c values of 8.8% (control) and 8.7% (intervention), respectively. In the younger subgroup (<65 years old), A1c improved more in the intervention arm (-0.5% vs. -0.2%, p=0.03) though the reverse was seen in patients ≥ 65 who actually performed better in the control group (-0.1% vs. -0.5%, p=0.008). The latter could have been because HCPs are so worried about hypoglycemia that they are backing off too much from appropriate therapy.

All measures of nocturnal hypoglycemia, too, were significantly lower following intervention with FreeStyle Libre vs. SMBG. For context, patients: (i) spent ~17 minutes fewer < 70 mg/dl (p=0.0001); spent roughly seven minutes fewer < 55 mg/dl (p=0.003); and (iii) spent roughly five minutes fewer < 45 mg/dl (p=0.004). While some may question these numbers and “lower” overall – we stress that any time at all not spent in severe hypoglycemia is a big win.

Table: Time in Hypoglycemia (hours per 24-hour day)

Glucose Level

Intervention Group Baseline (days 1-15)

Intervention Group Final (days 194-208)** ^

Difference (vs. control) in change from baseline

P-value

<70 mg/dl

1.30

0.59

-0.47

P=0.001

<55 mg/dl

0.59

0.19

-0.22

P=0.001

<45 mg/dl

0.32

0.08

-0.14

P=0.001

* Note: Abbott did not report the time in nocturnal hypoglycemia for the control group at either baseline or final study period. **Similar baseline and final results were not reported for the control group. ^ The study had a 15-day run-in with blinded CGM to determine baseline control, followed by a 180-day study period (SMBG vs. FreeStyle Libre), and then a 15-day masked CGM phase in the control group vs. 15 more days of FreeStyle Libre.

Table: Time in Nocturnal Hypoglycemia (hour between 11 PM and 6 AM)

Glucose Levels

Time in Nocturnal Hypoglycemia (hours between 11 PM and 6 AM)

P-value

Intervention Group Baseline (days 1-15)

Intervention Group Final (days 194-208)

Difference (vs. control) in change from baseline

<70 mg/dl

0.55

0.49

-0.29

P=0.0001

<55 mg/dl

0.27

0.18

-0.12

P=0.003

<45 mg/dl

0.16

0.08

-0.08

P=0.004

* Note: Abbott did not report the time in nocturnal hypoglycemia for the control group at either baseline or final study period

FreeStyle Libre pretty much completely replaced blood glucose testing, suggesting a high level of confidence in the factory-calibrated sensor. SMBG frequency with FreeStyle Libre fell from a mean of 3.8 tests/day at baseline to 0.3 tests/day (one every three days) at six months. Patients in the FreeStyle Libre arm scanned for glucose 8.3 times per day, which is once every two waking hours (Certainly more real-time glucose data than they were getting with SMBG, but probably not as much as type 1s will scan). The trend is a testament to the real-world accuracy of FreeStyle Libre in patients on insulin therapy. As a reminder, FreeStyle Libre’s label recommends confirmatory fingersticks : (i) during times of rapidly changing glucose; (ii) when hypoglycemia or impending hypoglycemia is reported by the system; or (iii) when symptoms do not match the system readings. However, these data are a reminder that patients don’t do fingersticks with FreeStyle Libre in the real world, something we’ve hear since the system launched.

The control group maintained their level of blood glucose testing through the study – baseline: 4.0 test/day; six months: 3.0 tests/day.

Figure: Number of FreeStyle Libre Scans and Blood Glucose Tests Per Day

FreeStyle Libre improved quality of life and patient-reported outcome measures, per two separate metrics. Diabetes-Treatment-Satisfaction Questionnaire results showed an increased overall treatment satisfaction for FreeStyle Libre vs. SMBG (13.1 vs. 9.0; p<0.001), while the Diabetes Quality of Life (DQoL) survey also showed increased treatment satisfaction for FreeStyle Libre vs. SMBG (-0.2 vs. 0.0; p=0.03). We absolutely loved how Abbott reported these outcomes and would urge the field to decide together on how to report this data and move toward standardized reporting.

No device-related serious adverse events were reported. Overall, 520 adverse events were reported during the course of the study; of these, only nine (reported by 6 subjects) were related to the device. According to Abbott, all nine events were related to an adhesive reaction, allergy, rash, or local infection at the sensor site and quickly resolved. This corroborates some patient reports on Twitter complaining about the adhesive – this is to be expected with any technology like this, and we assume Abbott is thinking about how to improve the adhesive in next generations although there’s not really a lot they have to do as most patients are not experiencing problems.

Close Concerns’ Analysis

The A1c results are underwhelming in terms of the primary outcome of A1c, given the 8.8% baseline and given the enormous patient and HCP enthusiasm associated with the device. We had been hoping for population-wide improvement and it’s disappointing that patients ≥65 years old saw improved glycemic control on SMBG, though as noted – unless patients are working with HCPs to respond appropriately to date, of course their A1cs will not necessarily improve – that is not to detract at all from the importance of hypoglycemia reduction! The small incremental A1c advantage (0.3%) in FreeStyle Libre patients <65 years was also lower than we would have expected overall and raises the case whether Libre might be more apt to focus patients on avoiding hypoglycemia rather than hyperglycemia – that is addressable without a doubt in our view.

The study design did not use a per-protocol mandatory insulin adjustment (i.e., not treat-to-target), which would have unquestionably improved the magnitude of A1c benefit. Providers and patients could decide what to do with the data at their regular visits, a deliberate decision to ensure a “real-world trial”. That was a very tough call, and given the A1c endpoint, we believe it would have been smart to include a treat-to-target component.

As we have been doing for multiple years, we point out the limitations of A1c as a yardstick for real-world value. A1c is of course an incomplete metric and one that is obscured by changes in hypoglycemia. Glucose control for many patients is not defined just in terms of this measurement but in terms of time-in-range, averages as well as standard deviation glucose data, quality of life, fear, hospitalizations, etc. The most successful therapies will improve value across the board and FreeStyle Libre is definitely passing the ultimate test of a product: demand has exceeded supply! Indeed, last year’s capacity constraint speaks to the way Libre is absolutely helping patients, and we imagine we are likely not seeing the real-world efficacy of Libre in the RCT setting. As a side note – we’ve heard here in Milan that patients who have Libre can now order up to six sensors at once and the elation we’ve heard associated with this change has been quite compelling.

Medtronic’s OpT2mise trial of pumps in type 2 is an interesting comparator on the A1c and hypoglycemia fronts. That study enrolled a population with a baseline A1c of 9.0% and doing 2.5 SMBG tests per day (slightly worse than this trial, but not by much). The trial showed an A1c reduction of 1.1% with an insulin pump vs. 0.4% in the MDI group (p<0.001) after six months, though hypoglycemia was not improved in the pump group.

What would the A1c outcome have looked like in REPLACE if hypoglycemia was unchanged? Put differently, what is a bigger success? A 1% decline in A1c and no change in hypoglycemia, or no change in A1c but a 50% reduction in hypoglycemia? For payers, arguably the latter has better short-term payoff.

Was hypoglycemia in older patients + provider bias at work? We wonder whether clinicians were discovering a lot of undocumented hypoglycemia with FreeStyle Libre in the elderly and backing off treatment. We would point out that Abbott’s Ambulatory Glucose Profile does draw attention with red traffic lights to problem areas, and it’s certainly easier to improve hypoglycemia (back off insulin, eat more) than to improve hyperglycemia. Were providers drawn to the hypoglycemia? Did they prioritize fixing that over reducing mean blood glucose? That certainly seems like a likely explanation to explain the lack of an A1c improvement in the older group – and we see this as addressable.

Did older patient scan less frequently? This was our first thought, but the opposite was actually true: older patients scanned more often than those in the younger cohort (8.4 times/day vs. 8.0 times/day). We do wonder whether patients’ perception of success is more associated with avoiding hypoglycemia than hyperglycemia – probably!

To better understand REPLACE’s A1c data, we would love to know what proportion of patients improved their A1c by 0.5% or more? BY 1% or more? By 2% or more? What percentage of patients improved their A1c by 0.5% or more or reduced hypoglycemia by 30% or more? Were there “responders” and “non-responders” to FreeStyle Libre? Or was the small magnitude of A1c improvement consistent across the board?

Despite the underwhelming A1c findings, the hypoglycemia improvement lived up to its billing. All measures of hypoglycemia (day+night and nocturnal) were significantly lower with FreeStyle Libre, and it’s quite evident that these results are clinically meaningful – minutes of hypoglycemia saved daily translate to YEARS of healthy complication-free life later, particularly in the <45 mg/dl zone. For context, we the results seem somewhat comparable to those of the ASPIRE in-home study of the MiniMed 530G – and that device was taking action by suspending insulin! That trial showed a 32% reduction in nocturnal hypoglycemic events and a 38% reduction in mean area under the curve of nocturnal hypoglycemia events without an increase in A1c levels.

We found the significant reduction in time spent < 45 mg/dl particularly striking given how dangerous that range is. Even changes in a small number of minutes spent in that low range there could mean many healthcare dollars saved annually – we have to imagine that that is one of the most compelling takeaways for Abbott and would form the crux of any payer pitch.

We were impressed, too, to see the improvement in overnight hypoglycemia improvement – even without alarms with FreeStyle Libre! The finding implies that patients don’t have to have alerts to improve the overnight period … they just need the data, and then they can adjust therapy to create success.

In summary, Abbott’s full results strike us as quite solid – not a smashing success but certainly not a failure. Our gut reaction was disappointment (as we’re sure it was for many) but some perspective is needed; the data could have been worse (imagine if Abbott had hit its primary endpoint with a 0.4% reduction in A1c but increased hypoglycemia?) and could have been better (imagine if Abbott had picked hypoglycemia as the primary endpoint?). In the big scheme of things, these results likely fall somewhere in the middle of the road – we think it’s more likely that the long-term implications will be defined by the questions Abbott asked and lessons the company (and others) learn rather than missing the primary outcome. While we very much would’ve loved to have seen a 1% A1c reduction or at least the 0.5% A1c reduction that usually implies success, this is a more complicated story and given the enormous enthusiasm surrounding the product, we believe those are the design front will be diving in

Speaking of the long-term implications, we are unclear what the results mean for future reimbursement of FreeStyle Libre in type 2. What would payers say about this data? Certainly, there is a high EU bar for cost-effectiveness and added benefit, though CGM is getting some reimbursement in Europe (and FreeStyle Libre is cheaper than CGM – about half the price). How will Abbott proceed with this data? When combined with the results fro IMPACT in type 1, could it form the basis for reimbursement in some major markets? Or will the company need to pursue additional studies to supplement these findings? And speaking of additional studies, we can’t help but wonder what FreeStyle Libre might look like in the real world, complemented by the right drugs and the right behavior. It could do so, so much!

We also have to think that the reasonably positive findings here mean that Abbott’s six-month study in type 1s (primary outcome: hypoglycemia) is even more likely to be a smashing success. That FreeStyle Libre was able to achieve a hypoglycemia improvement and partial A1c improvement in the much tougher type 2 population bodes well for type 1. As a reminder, Abbott will present findings from IMPACT at ADA 2016.

Ultimately, we salute Abbott for ambitiously pursuing an outcomes study and testing these uncharted waters. A1c remains the metric-of-choice in the eyes of payers and despite the surface-level disappointing results, it’s not clear that less-ambitious-but-more-impressive results would have delivered a no-brainer decision. Instead, we think the results serve as an important lesson and valuable learning experience as companies begin thinking about study design and about engaging with reimbursement bodies. The ultimate goal is to increase the increase the number of people who would benefit from this technology, and moving forward, it’s absolutely critical to think about what is best for different populations.

Close Concerns’ Questions

Were there “responders” and “non-responders”? What proportion of patients improved their A1c by at least 0.5% OR reduced time in hypoglycemia by 30%+? Was there anyone in the trial that saw no benefit on A1c or hypoglycemia?

What would the A1c outcome have looked like in REPLACE if hypoglycemia was unchanged? What is a bigger success from a payer perspective? A 1% decline in A1c and no change in hypoglycemia, or no change in A1c but a 50% reduction in hypoglycemia? Which would a payer prefer? Which would a provider prefer? Which would a patient prefer?

How would these results have looked with FreeStyle Libre Pro used intermittently instead of real-time data?

In retrospect, what would Abbott change about the study design? Should sites have been mandated to make insulin adjustments based on the data? Should the study have enrolled patients who weren’t already checking their blood glucose so regularly?

What are the implications for reimbursement? How will payers receive the data? Will the magnitude of the benefit be enough to show cost-benefit? What will Abbott do going forward?

What are the implications for IMPACT in type 1? Should these results raise our expectations for what we’ll see in terms of hypoglycemia reduction in type 1 patients?

What can be learned from this trial for future studies? How should the diabetes technology field think about designing outcomes studies for reimbursement? What should closed-loop investigators take away from this trial?

FreeStyle Libre - Nightscout Update

Separately, we’ve learned that Nightscout users in Italy have built FreeStyle Libre remote monitoring via an Android app, Glimp. Glimp has existed for some time as an unauthorized app for reading the FreeStyle Libre sensor (we wrote about it last October), though Nightscout users in Italy are now using it to remotely monitor patients on FreeStyle Libre. A major win for parents, and the app can also send readings to HCPs. The instruction manual is posted within the Nightscout Italy Facebook group (which requires permission to enter). Even with Abbott’s LibreLink Android app for reading the FreeStyle Libre sensor (limited launch in Sweden in November), it does not enable remote monitoring. We hope that the addition of a pediatric label will move Abbott to add remote monitoring to LibreLink in the future – parents love Dexcom Share and MiniMed Connect. It’s worth noting that Glimp is an unauthorized app with fairly good reviews (4.3/5.0, 151+ ratings), though it does reveal the downsides of patients hacking into devices themselves – the FreeStyle Libre reader makes some corrections to the raw sensor data, so Glimp does not display the exact same value as the reader (“it’s close,” notes the reviews). Of course, parents will only use it if it works, and it seems like it does based on the reviews.

Clinical Accuracy Evaluation of Freestyle Libre Flash Glucose Monitoring System When Used By Children and Young People with Diabetes

Fiona Campbell, MD (Leeds Teaching Hospitals Trust, UK)

Dr. Fiona Campbell shared data from Abbott’s 89-patient, 14-day EU pivotal trial of FreeStyle Libre in pediatrics, which demonstrated an MARD of 13.9% vs. capillary fingersticks (the study had 5,493 paired sensor-fingerstick points). The data were impressively consistent across the board as 84% of points were in Zone A of the Consensus Error Grid and 16% in Zone B, a testament to the device’s accuracy as patients would experience it (i.e., relative to fingersticks). The data represent a slight downtick on what has been achieved in the EU pivotal trial where Libre demonstrated an overall MARD of 11.4% vs. FreeStyle Precision BGM (n=13,195 paired points) though given the vagaries of fingersticks in pediatrics patients, we would argue that the overall accuracy is highly encouraging. Abbott will need to maintain those results at scale – we have little doubt on that front at this stage, but factory calibration is of course not easy.

Abbott announced earlier during ATTD that it has received CE Marking for the pediatric indication of FreeStyle Libre. We assume this data was used in the submission.

The pediatric study was conducted a bit differently relative to the previous US and EU adults studies. The trial enrolled patients at nine centers across the EU in type 1 patients on insulin therapy. Patients wore two sensors on the back of their arm for 14 days and were asked to: (i) perform four capillary blood glucose tests daily; and (ii) scan the sensor following each test. [Note: They were not asked to attend in-clinic YSI sessions.] Notably, Dr. Campbell shared that patients had a mean baseline A1c = 7.7%, ranging from a low of 5.6% to a high of 10.4% for a nice mix of well-controlled and out-of-control patients.

Dr. Campbell noted that the glycemic variability seen in the study was comparable to the variability seen in other pediatric CGM studies, stressing that the sensor was tested across the full range of reasonable sensor values.

MARD was not broken down by glucose range, so accuracy in hypoglycemia is an unanswered question. The product label has not changed other than the pediatric indication, so we assume it will still recommend a confirmatory fingerstick when patients are hypoglycemic. Still, patients in the real world clearly trust the device enough to test rarely, so we have little concern about the hypoglycemia data in this study.

Dr. Campbell shared positive data from user/caregiver experience questionnaires of FreeStyle Libre in the study. There was no specifics on how these questions were asked though answers could vary between: Strongly Agree /Agree /Neutral /Disagree/ Strongly Disagree. The data certainly point to why European patient uptake has been so strong in these early days, especially in those that have avoided current CGM due to comfort/wearability. The data below were for the “Strongly Agree” answer choice.

It did not hurt when the sensor was put on. Girls, 84% (Strongly Agree) - Boys, 84% (Strongly Agree)

It was easy to put the sensor on. Girls, 91% - Boys, 93%

I did not mind wearing the sensor on my arm. Girls, 93% - Boys, 98%

It was comfortable to wear the sensor. Girls, 88% - Boys, 66%

It was easy to scan the sensor. Girls, 100% - Boys, 100%

It was more comfortable [than BGM]. Girls, 93% - Boys, 95%

It was less painful [than BGM]. Girls, 91% - Boys, 85%

It was more private [than BGM]. Girls, 83% - Boys, 88%

It was quicker to check my blood glucose. Girls, 100% - Boys, 95%

It was easier to use. Girls, 98% - Boys, 98%

It did not get in the way of my daily activities. Girls, 88% - Boys, 85%

I liked how my glucose readings were shown on the screen. Girls, 88% - Boys, 90%

It gave me more information than my current glucose meter to take care of my diabetes. Girls, 71% - Boys, 68%

I would recommend it to someone else with diabetes. Girls, 95% - Boys, 98%

Dr. Campbell also shared positive data from provider experience questionnaires of FreeStyle Libre in the study.

100% agreed that the report’s visual presentation means I would be able to effectively share information with my patients/caregivers.

100% agreed that the reports present information in such a way that I would be able to engage patients/caregivers with the information.

100% agreed that the reports help me identify glucose trends that are not visible with BGM data and could potentially support informed therapy decision.

100% agreed that the reports help me to assess the effectiveness of my patient’s current therapy.

78% agreed that the reports help me identify hypoglycemic risk.

100% agreed that the reports allow me to easily determine how much time my patients’ glucose level is within their target range.

89% agreed that the reports help me to easily identify post-prandial trends.

89% agreed that the reports provide insight to frequency, duration, and pattern of hypoglycemic events.

100% agreed that the reports provide insight to frequency, duration, and pattern of hyperglycemic events.

Very few adverse events were reported among patients in the study – 44 subjects reported any sort of discomfort related to the sensor insertion and all reports were consistent with what would be expected following insertion of a sensor into the skin. There were no severe adverse events reported and all patients were able to see the trial to conclusion.

Unsurprisingly, Dr. Campbell shared sky-high enthusiasm for FreeStyle Libre. Asked in Q&A which patients she would recommend Libre to, Dr. Campbell did not skip a beat: “ALL of them!”

Questions and Answers

Q: Can you talk about the data in hypoglycemia and hyperglycemia?

A: I haven’t shown this here. There is still a lot of data to come out of this. This was preliminary data that I showed today. There will be more to do to evaluate all of that.

Q: What percentage of pediatric type 1 patients would you recommend Libre for?

A: All of them!

Q: Do you think FreeStyle Libre should replace CGM?

A: I’ve had a lot of people asking me that. CGM is acceptable for some but not all people and we know that there are difficulties getting young people to comply with alarms. Libre is straightforward and has no alarms. I would say that Libre should replace SMBG. However, it’s a real discussion when thinking about the patients that would succeed on CGM vs. FGM. I think about it as yet another addition to our diabetes armamentarium.

Accuracy and Longevity of an Implantable Continuous Glucose Sensor in the PRECISE Study: A Prospective Multi-Center Pivotal Trial

Hans DeVries, MD (Academic Medical Center, Netherlands)

Dr. Hans DeVries presented full 90-day data (n=71) from the EU pivotal trial of Senseonics Eversense implantable CGM sensor, on-body transmitter, and mobile app. Overall MARD vs. YSI at ten in-clinic visits was 11.5%, nearly identical to the interim results (n=44) shown at DTM last fall. Accuracy still diminished in the hypoglycemic range (<75 mg/dl), where overall MARD was 20%. Still, the Clarke Error Grid showed a strong 85% of measurements in Zone A. Sensors were fairly durable, with 82% making it to 90 days, and though we have long criticized the on-body transmitter, compliance with wearing it was excellent: a median 23.5 hours of wear time per day. Patients even saw a 0.5% decline in A1c from a baseline of 7.6% (p=0.051; no control group obviously, but an encouraging result). Six-month data will be presented later this year, and as of our trip to the exhibit hall on Wednesday, Eversense is still pending a CE Mark. Senseonics has already learned from this data and improved the algorithm’s MARD to 10.5%, which is being used in the just-initiated US pivotal study. Dr. DeVries also revealed that FDA is requiring a blinded sensor in the US pivotal study. We had not previously known that and are baffled by that decision. The big question for Senseonics is whether it can expand the EU and US glucose sensor markets, where competition is fierce with Abbott’s FreeStyle Libre, Dexcom’s G5, and Medtronic’s 640G (EU) and 670G (coming). Does Eversense’s on-body transmitter negate the implantable advantage in those naïve to wearing things on the body? (This trial wasn’t a true test of that, as 32% of study participants had used a CGM and 42% were on a pump before this study.) Will cost be similar to current CGM? How hard will it be to make the sensor at scale and train providers to do the insertion? The company has clearly come a long way on a supremely challenging problem, and of course, it has to walk before it can run to next-gen systems.

t1d Exchange Survey on Pump and CGM discontinuation

Viral Shah, MD (University of Colorado, Aurora, CO)

A T1D Exchange survey found that patients’ top-cited reasons for discontinuing pump or CGM therapy included problems with insertion/adhesive, cost/lack of insurance coverage, and inaccuracy (for CGM). Dr. Viral Shah (University of Colorado, Aurora, CO) presented data from an electronic survey of 2,452 adults with type 1 diabetes that aimed to identify human factors associated with pump and CGM discontinuation. In this cohort, 67% of patients were currently using a pump, 31% were not using a pump, and only 2% had discontinued within the past year. 30% of patients were current CGM users, 59% were not using CGM, and 11% had discontinued within the past year. The demographic factors significantly associated with pump discontinuation were younger age (under 26), infrequent blood glucose testing, and lower income and education level. The top-cited reasons for pump discontinuation (patients could select more than one reason) were problems with insertion/adhesive (60%), cost/lack of insurance coverage (45%), and interference with sports (42%). For CGM, lower income level was the only demographic factor significantly associated with discontinuation. Interestingly, patients who reported testing their glucose more frequently were more likely to discontinue CGM, though the association was not significant. Dr. Shah’s hypothesized that these more engaged patients likely didn’t trust that the CGM measurements were accurate. This is consistent with the finding that inaccuracy/device malfunctioning was the most commonly cited reason for discontinuing CGM (cited by 71% of participants), followed by insertion/adhesive problems (61%) and cost/lack of insurance coverage (58%). When asked during Q&A, Dr. Shah noted that the CGM discontinuation rate was higher with Medtronic devices compared to Dexcom, but he did not provide specific numbers. With the caveat that this was a small sample from a fairly unrepresentative cohort (the Exchange is an earlier adopter population at top clinics), such human factors information should be very useful for setting patient expectations, training patients, and for companies aiming to design more patient-friendly devices.

Blood Glucose Sensing Through Skin By Non-Invasive Finger Touch Meter

Tarun Kakkar, PhD (University of Leeds, UK)

Dr. Tarun Kakkar shared an unconvincing overview of Glucosense’s non-invasive glucose meter: a MARD of 29% vs. fingersticks (77% in Zone A of Clarke Error Grid); a ~30-second measurement time for each spot reading (it’s not continuous); no data in the hypoglycemic range (<70 mg/dl). This company has been in stealth mode for some time, and we had heard speculation that they were working on glucose monitoring; we valued the public presentation, though it sounds like the company has an uphill battle on many fronts (accuracy, form factor, hassle). As we learned, Glucosense’s flagship product is a non-invasive device that fluoresces in the infrared region when stimulated by a low power laser. The glass chip is placed in contact with the patient’s skin and the reflected fluorescence signal varies based on the concentration of glucose in their blood. The device is designed to fit in the palm of a patient’s hand (see a picture below) and Glucosense’s current product roadmap includes adding cloud connectivity (wireless data transfer to a smartphone) and a device for continuous glucose monitoring (not mentioned in the presentation but highlighted on the company’s website). Glucosense remains early stage and while early returns aren’t clinically accurate enough, we salute the team for forging ahead in the extremely challenging non-invasive glucose-monitoring field. We do think the approach is worth pursuing for patients though the bar is getting higher considering the nearly non-invasive offerings from Abbott (FreeStyle Libre) and the potential Dexcom/Google offering (flexible, disposable, bandage like CGM the size of a penny). For now, many questions remain for Glucosense: How should the company trade off accuracy vs. improved form factor vs. cost? At what point does the device’s clinical inaccuracy outweigh any potential benefit of more frequent monitoring? How will the regulatory pathway shake out? How expensive is manufacturing?

Glucosense Non-Invasive BGM

Posters

A Medtronic poster offered the most details ever on its fifth-generation sensor (i.e., Enlite 4), featuring one calibration per day, 10-day wear, and a strong overall MARD of 10.9% vs. the Bayer Contour Next Link meter (n=55 sensors, 5,709 evaluation points). We had not ever known this would be 10-day wear or one calibration per day, though that would exactly match Dexcom’s plans for G6. The fifth-gen CGM (!) includes a 90-minute warm up, redundancy via two sensor flexes, a proprietary fusion algorithm to combine the two outputs, and intelligent diagnostics to assist with fault detection and sensor health. The poster showed the standalone Guardian Connect setup we mentioned on day #1, featuring a Bluetooth-enabled CGM transmitter and a smartphone app display (no receiver or pump); as a reminder, the Enlite 3 version of this system is under CE Mark review in Europe and expected to launch by April 2017 in the US. This accuracy study included 25 participants with diabetes who wore up to four sensors on the abdomen or arm for 10 days. At three in-clinic session (Days 1, 7, 10), meal challenges were administered and blood glucose measurements were recorded every 15 minutes for three to four hours with the Bayer Contour Next Link meter. Participants were also asked to take 8-10 blood glucose measurements daily when at home. Overall MARD was 10.9% (11.7% on the abdomen and 9.9% on the arm), including a day #1 MARD of 12.6%. Roughly 45% of sensors had a MARD <10%, with most of the remaining sensors between 10% and 15%. Mean absolute difference (MAD) in hypoglycemia (<70 mg/dl) was 12 mg/dl, and 86% of overall points were within 20 mg/dl or 20%. Sensors were removed from analysis early due to adhesiveness or battery failures – the percentage was not specified, and both are critical question marks for Medtronic’s clamshell transmitter design (larger on the body and less secure than Dexcom and Abbott sensors). While this is still a feasibility study, this sensor shows a marked improvement from the original Enlite, helping Medtronic catch up to Abbott and Dexcom’s more accurate sensors.

Medtronic also displayed accuracy data from a pre-pivotal study of its fourth-generation sensor (Enlite 3), to be used with the MiniMed 670G or the Guardian Connect mobile app. It demonstrated an MARD of 11% vs. YSI based on two fingerstick calibrations per day (days 1, 3, 7 visits; YSI values recorded every 15 minutes for 12 hours; 4,805 paired points). The accuracy was much stronger on the arm (8.7%) vs. the abdomen (11.9%-12.6%) – Abbott clearly figured that out too with FreeStyle Libre. The seven-day wear Enlite 3 sensor has an improved algorithm with intelligent diagnostics that determine if it is safe to enter closed loop. The algorithm will also request a calibration when the system detects the overall performance can be improved, and data is not displayed when it detects poor sensor performance. It’s great to see these safeguards in place. In the oral presentation discussing the in-clinic US pivotal study of the MiniMed 640G, Enlite 3 demonstrated an MARD of 12.6% on the first day; further performance was not mentioned, though that was consistent with the pre-pivotal’s day #1 MARD (12.9%). In that study, the 640G was not quite as strong in avoiding hypoglycemia (60% of low limit events avoided vs. ~75-80% in other studies), though the hypoglycemia induction protocol made the study far more challenging and less real world. Every EU patient we’ve talked to on the 640G loves it – one told us he’s had 0% time in hypoglycemia and 80% time-in-range over the past several months. As a reminder, we learned at JPM that Medtronic is likely to skip the 640G/Enlite 3 in favor of launching the 670G/Enlite 3 in the US first. The pivotal study for the 670G will wrap up around the end of February.

Industry Updates

FreeStyle Libre EU Pediatric Indication

Abbott announced that it has obtained a CE Mark for a pediatric indication of FreeStyle Libre, allowing the company to market the system to children 4-17 years old (previously only 18+ years). Many pediatric patients seem to already be using the system off label in Europe, so we’re not sure if this has significant commercial implications (FreeStyle Libre is sold online without a prescription, so anyone can buy it, including parents). That said, it is excellent for Abbott to get the official label and we surmise that the indication may be of very real value down the road – Abbott, after all, is pursuing reimbursement in type 1s and type 2s and a pediatric label would be critical for coverage across the age spectrum. [As a reminder, Abbott is presenting its six-month reimbursement study in type 1s at ADA 2016.] The approval does enable Abbott sales reps to call on pediatric endocrinologists that were previously off limits and helps Abbott stay competitive with Dexcom’s G5 that is approved down to age two. Abbott has yet to disclose FreeStyle Libre sales at this point, so we won’t know how much this increases sales from the current base. As we understand it, there will no differences in the sensor or packaging except of course for the updated label; no promotions have been announced at this time, though we imagine the “No Fingersticks” will resonate soundly with the pediatric population. It’s hard to know if the news has any implication for the labeling of the US product (which we recently learned could launch “toward the end of this year”) and Abbott has remained tight-lipped on its future plans. We’re hoping we’ll learn more tomorrow when the company is sharing the full pediatric accuracy data that was submitted for the indication in an afternoon oral.

Is It Time To Move To Time In Range As The Main Glycemic Control Measure?

It Is Time To Move To Time In Range(s) As The Main* Measure Of Glycemic Control

Aaron Kowalski, PhD (Chief Mission Officer, JDRF, New York, NY)

Dr. Aaron Kowalski enthusiastically supported using time-in-range as the main measure of glycemic control, and more broadly, asserted that interventions must balance “diabetes health” and “diabetes happiness.” His closing slide showed him running a marathon with type 1 diabetes, summarizing the presentation aptly: “A1c is not what I’m thinking about when I’m at the starting line.” Dr. Kowalski’s talk noted many of the limitations of A1c, highlighted the intuitive advantages of time-in-range (though some challenges to iron out), and mentioned JDRF’s new T1D Outcomes Program, which aims to define the metrics of importance to people with type 1 diabetes, providers, researchers, industry, FDA, and payers – the steering committee includes all the major professional associations, and we sincerely hope this can move the needle on defining outcomes beyond A1c, and more importantly, getting them accepted. Following the advocacy success of getting time-in-range into the FDA artificial pancreas guidance, JDRF is now working on a “similar pathway for drugs and biologics.” Now that could be impactful, particularly for non-insulin interventions for type 1 like SGLT-2 inhibitors or ultra-rapid insulins. More broadly, Dr. Kowalski’s talk reiterated many of the elements of his Diabetes Scorecard (Diabetes Care 2015), emphasizing the need for better “value” in type 1 diabetes, which is defined differently for patients, providers, and payers – and is not just A1c, but includes device burden, time investment, fear, provider quality metrics, hospitalizations, etc.! The most successful therapies will improve value for all three stakeholders; we wonder if automated insulin delivery can meet that bar.

Dr. Kowalski noted the limitations of A1c, despite its status as a validated surrogate for long-term outcomes: (i) long-term measurement – not reflective of day to day; (ii) not very actionable; (iii) not reflective of hypoglycemia; (iv) not reflective of variability; and (vi) not informative regarding glucose perturbations cause and effects.

Dr. Kowalski called time-in-range much more intuitive, as it provides: (i) both hyperglycemia and hypoglycemia transparency; (ii) direct visibility to both short-term and long-term diabetes risks; (iii) a more physiologic target for improved glycemic control; and (iv) the best representation of diabetes glycemic health.

Still, Dr. Kowalski acknowledged that there are a few nuances to time-in-range that must be ironed out: (i) What is the ideal range? (is it 70-180 mg/dl, which is generally accepted in the artificial pancreas world and by FDA? Or is it 70-105 mg/dl, the non-diabetes physiological range?); (ii) What is the goal – how much time should be spent in each range?; and (iii) time-in-range is CGM-dependent to a large degree; what do we do for those using BGMs alone?

In Q&A, Dr. Irl Hirsch pressed the panel for specific recommendations on time-on-range, to which Dr. Kowalski admitted it’s will be “very hard” – it might be better for clinicians to think in terms of improvement. For instance, it will be hard to come to a consensus on what threshold for time-in-range is optimal – 75%? 100%? Instead, one could look at simply improving time-in-range, or striving to reduce time-out-of-range. This seems a most valuable recommendation, since it is actionable, realistic, and could align much more with the value-based healthcare system toward which things are moving.

Dr. Kowalski ran through several examples of old, burdensome devices that may have improved glycemic control, but weren’t realistic for patients to wear in the real world (e.g., the infamous backpack dual-hormone artificial pancreas; the bedside Biostator; the “blue brick” auto-syringe insulin pump). For these devices, the ROI for patients wasn’t there to encourage wide adoption. By contrast, he noted that modern CGM devices (the slide showed Dexcom’s G5, Medtronic’s MiniMed 530G, and Abbott’s FreeStyle Libre) have dramatically improved the ROI for patients – and thus, will pave the way for greater effectiveness and greater adoption.

We Need Standard Definitions and Standard Glycemic Reports

Dr. Richard Bergenstal discussed the need for standardized CGM data reports – an “ECG for glucose patterns” – that incorporate information beyond A1c. He stressed that he does not advocate throwing out A1c entirely but suggested that, at least to start, clinicians should aim to optimize A1c while minimizing hypoglycemia. This could eventually be replaced by evaluating time in range and time in hypoglycemia. In a slide that would have been at home in a self-help book, he promised clinicians “four steps to transform your practice”: cut the cords (on old devices), aggregate blood glucose data from multiple devices, generate a standard report, and agree on an action plan (key word: agree). The rest of his presentation focused primarily on an example of a standard report, his Ambulatory Glucose Profile (AGP) developed with feedback from an expert panel he convened on the issue in 2012. The AGP is a one-page report with relevant glycemic numbers at the top, followed by a simple visualization of glucose patterns. In this talk, he focused mainly on which numbers should be included in the report, noting that is crucial to standardize the definitions of hypo- and hyperglycemia. His report includes percent time below 70 mg/dl, 60 mg/dl, and 50 mg/dl, which he suggested corresponds clinically to “low,” “very low,” and “dangerously low.” Similarly, he argued that reporting percent time above 180 mg/dl, 240 mg/dl, and 300 mg/dl is more useful for patients than lumping all the values together as hyperglycemia. He suggested that in a research setting, more complex measures like area under the curve that incorporate both the duration and severity of hypoglycemia could be even more useful. His main point was that this data needs to be standardized in some way, not that he is wedded to his particular method.

Escaping The A1c-Centric Role Of Assessing Glycemic Control In Diabetes

Medtronic Diabetes’ Dr. Bob Vigersky reiterated highlights from the outstanding talk he gave at DTM 2015 on novel visual and numerical representations for capturing composite diabetes outcomes (A1c, hypoglycemia, weight). He argued that composite scores are beneficial because they allow for the comparison of efficacy across different types of interventions – pharmacologic technologic, and psycho-educational. To illustrate this point, Dr. Vigersky reviewed an impressive range of visual and numerical representations of composite outcomes from a variety of studies. His discussion included (i) the glucose pentagon (DT&T 2009 and JDST 2012), a single graph and number combining five elements of glycemia (A1c; SD; time >160 mg/dl; AUC > 160 mg/dl; and mean glucose); (ii) the Q-score (BMC Endocrinologist Diab 2015), a single numerical value combining five primary factors that determine CGM profiles (central tendency, hyperglycemia, hypoglycemia, intra- and inter-daily variations); and (iii) his own novel approach (published last year in JDST) combining A1c, hypoglycemia, and weight change in a single score out of 100. Echoing his concluding commentary from DTM 2015, Dr. Vigersky advocated for “escaping” the A1c-centric world in evaluating diabetes interventions and working with regulatory bodies, clinicians, and industry to agree on a composite metric to better describe overall glycemic control. We agree that this is particularly essential for many next-gen therapies such as CGM and closed loop devices, which may not show improvements in A1c but do reduce hypoglycemia and improve time-in-range.

COMPOSITE MEASURES OF GLYCEMIC CONTROL

David Rodbard, MD (Biomedical Informatics Consultants Potomac, MD)

Dr. David Rodbard argued that it is time to switch from A1c to measures of time-in-range when evaluating new therapies, highlighting a series of graphical methods for displaying glucose values. He stated that A1c, mean glucose, and % time in range alone are not sufficient when comparing interventions; instead, efficacy and safety should be evaluated simultaneously using one of six graphing methods: risk of hypoglycemia vs. A1c, % high vs. % low, change in % high vs. change in % low, triangular plot (% low vs. % target vs. % high), hypoglycemia index vs. hyperglycemia index, and risk of hypoglycemia vs. A1c/mean glucose. Dr. Rodbard provided a series of examples of these comparisons, stressing the value of the triangle plot for its ability to perform a multi-dimensional analysis (the three points represent 100% low, 100% in-target, and 100% high). He also showed a graph of % high vs. % low, where target glucose values fall at the origin, and a graph of change in % high vs. change in % low, which creates quadrants that correspond to (i) an increased risk of both hyper- and hypoglycemia; (ii) a decreased risk of hyperglycemia but increased risk of hypoglycemia; (iii) decreases in both hypo- and hyperglycemia; and (iv) decreased hypoglycemia but increased hyperglycemia. According to Dr. Rodbard, these methods are feasible, practical, and informative, and can facilitate rapid analysis of risks of hypo- and hypoglycemia simultaneously. Dr. Rodbard recently published these approaches for comparing therapeutic interventions (JDST 2015), and we salute him for thinking outside the box on other ways to present diabetes metrics. It may take years for the diabetes community to adopt a time-in-range or a composite outcome (similar to how long it took A1c to gain credibility), though we are very pleased to see the increased focus on this topic at ATTD 2016.

Panel Discussion

Dr. David Klonoff (Mills-Peninsula Health Services, San Mateo, CA): We’ve heard A1c by itself is not enough. But with a composite outcome score, would we miss out on the individual components?

Dr. Vigersky: I think A1c could be replaced by time-in-range. It makes sense. What I didn’t show was that with the Q-score, you can select out areas of concern that can be addressed with that score in a graphic way. Bar graphs can be generated for the most important elements, like standard deviation or hypoglycemia. These can be easily generated from the data that exists.

Dr. Bergenstal: I am all for an aggregate score, and I thought this symposium was amazing. On an individual basis, however, I would plea that we never get away from having conversations around the actual profile, a person’s life picture.

Dr. Vigersky: I wouldn’t argue with that at all. We have a hard time explaining A1c to patients. We’ll have an equally hard time explaining whatever metric we choose. For studies, payers, and regulators, however, we can’t show a picture – we have to show them numbers.

Dr. Rodbard: You have high, low, in target range, average, and variability. I’m an advocate of time-in-range. If you have a high percentage in the target range, you need to have a mean glucose in the center of the range, and you need to have small variability. Conversely, if you have a mean in the center and small variability, you have a small percentage of low and highs. But you want to know, “Where is my biggest problem – lows, high, or variability?”

Q: One of the things that struck me was that you are striving hard to come up with composite measures for glucose. However, Aaron showed that on a patient basis, one of the most useful things to have is a temporal glucose profile to show trends throughout the day, and particularly what’s going on at night. Composite measures lose some of that information. A new technique that has come out recently is the functional data analysis technique, which allows temporal glucose profiles to be analyzed at a population level where you can determine the significant differences between interventions and determine where these differences are occurring. We published this in Diabetes Care last year, but it might be useful to know about.

Dr. Kowalski: It comes back to simplicity. This audience is self-selected for early adopters and technophiles, and the fact that we still have to explain A1c is telling. There’s something to be said for simplicity. In other audiences, such as regulatory, there’s a place for deeper complexity. But in the clinic, simple is better.

Dr. Irl Hirsch (University of Washington, Seattle, WA): As we’ve been sitting here, we all recognize that A1c does not tell us enough. It’s actually a little more complex. In the ADAG study, we saw that if you have an A1c of 8%, and I have an A1c of 7%, it’s quite possible that your mean blood glucose is lower than me, because we glycate hemoglobin differently. And there are 14% of people for whatever reason in which A1c doesn’t work – things like anemia. A1c has all kinds of problems. I think time-in-range is the way to go. But we’ve been talking about it in very broad strokes. If we’re going to talk about individualization of patient care, we need specifics. We need to look at time-in-range like we have a target A1c <7%. What is the target for time-in-range, amount of time in hypoglycemia, overnight, during day, or climbing a mountain. We need specifics as opposed to just continuing to talk about getting something more than A1c.

Dr. Kowalski: It’s really hard. If I think about it, it’s going to be very hard to set a euglycemic target. The tools do not allow people to get there. I think about better. So if you have hypoglycemia issues or hyperglycemia issues, can we reduce those.

Bergenstal: Coming to consensus on time-in-range will be tough. For instance, 3% hypoglycemia is fine, but is that under 70 mg/dl or under 50 mg/dl. It gets a little more complicated fast.

Brandon Arbiter (Tidepool): Time in range is a much more representative measure than A1c. Is having TIR dependent on wearing a CGM sensor? If only 10-15% of people with type 1 diabetes in the US are wearing it, what are the implications for trying to adopt time in range as a metric?

Dr. Kowalski: Everyone with type 1 should be on a CGM.

Psychological Outcome With Diabetes Technology

Psychosocial Outcomes Of CGM Use In Children And Teens With Type 1 Diabetes

Lori Laffel, MD, MPH (Joslin Diabetes Center, Boston, MA)

Dr. Lori Laffel shared one-year results from the CGMi trial evaluating the effectiveness of a “family-focused behavioral teamwork intervention” vs. standard education in the initiation of CGM in youth ages 8-17 with type 1 diabetes. Notably, discontinuation was driven by device choice more than psychosocial outcomes. The 24-month randomized control trial aimed to assess whether psychosocial support optimization could help overcome the barriers to CGM use and improve glycemic control. One-year findings demonstrated that ~30% of patients discontinued CGM use, higher than we would have expected (especially given the above study). However, Dr. Laffel shared that the discontinuation rate was independent of study cohort group (i.e., no difference between intervention and control group) and was instead predicted by CGM device. [As a reminder, the trial enrolled in 2013 when Dexcom was still rolling out its G4 – thus, some patients spent the entire 12-month period on the Seven Plus; some transitioned halfway to through the trial to the G4; some spent the entire 12-month period on the G4 – these are quite old products so this discontinuation rate is far less relevant overall.] Apparently, choice of device (G4 vs. Seven Plus) predicted both discontinuation rate and median hours/week CGM use in both groups: “It wasn’t psychosocial aspects of CGM that predicted outcomes. It was the device itself!” The conclusion was not meant to dismiss the importance of psychosocial factors but to highlight that fundamental deficits in devices themselves, as we have long said - e.g., technical glitches, false alarms, inconvenient insertion – still represent major problems and can be quite self-defeating. But think about the upside!

CGM Reimbursement In The Larger Countries – When Will It Come?

Will Medicare Deliver?

Claudia Graham, PhD (Dexcom, San Diego, CA)

Dexcom’s Dr. Claudia Graham was not able to provide a firm guidance on when we might see Medicare coverage of CGM though that did not stop her from delivering a scathing overview of the “RIDICULOUS” bureaucratic red tape muddling the process. This was one of the most dynamic presentations we have heard on the topic – one that is quite nuanced and complex – and we thought she did an outstanding job breaking down the disconnect between US private payers and Medicare for the international audience.As a reminder, Medicare’s primary objection to covering CGM stems from the adjunctive labeling (i.e., that treatment decisions be based on BGM readings rather than CGM readings). Dexcom had seemed close to overcoming this objection, though its most recent financial calls and JPM update suggested FDA discussions are still ongoing. Importantly, Dr. Graham stressed that clinical data alone will not be sufficient to support coverage of CGM, noting instead the ongoing “surround sound” approach that has brought patient, professional association, and industry groups together in an advocacy campaign. Indeed, we were struck by just how challenging the political angle to this problem is (how to deal with an agency – CMS – that isn’t responding to reason?), and we salute Dr. Graham and collaborators for continuing to drive awareness in Washington. As a reminder, bipartisan support of the Medicare CGM Access Act of 2015 continues to grow following the reintroduction in the Senate and House of Representatives in late March, though judging from Dr. Graham’s commentary, it sounds like the 2016 election cycle is going to complicate this picture in a big way.

A NICE Reassessment

Peter Hammond MD (NHS Harrogate and District, Harrogate, UK)

England’s Dr. Peter Hammond informed attendees that NICE’s assessment of sensor-augmented pump (SAP) therapy – which we believe will be the final word on whether the UK will adopt national coverage for SAP – has been delayed to March 2016 (the guidance was previously slated for last week). As we understand it, the assessment comes on the heels of what was a major reimbursement victory for diabetes technology this past August, when UK clinical guidelines recommended CGM for the first time in certain adults and children with type 1 diabetes (which centered on patients with lots of hypoglycemia, which sounded very right to us). The recommendation does not guarantee a positive ruling from NICE, but is certainly better than what we might expect from the tough agency in an area that needs more clinical data. It’s a big win that NICE has implicitly acknowledged CGM’s cost-effectiveness, at least in certain patients (while we certainly know – in spades! – the value is there, we acknowledge there is not enough data). Dr. Hammond suggested that NICE’s decision is hinging on the incremental benefit of standalone CGM vs. a sensor-augmented pump – if only Dexcom’s DIaMonD data was available to answer this question (expected later this year)! We’re not sure if the reimbursement decision will have implications for the artificial pancreas in the UK, since the clinical benefit will presumably be greater than SAP alone.

A Breakthrough in Germany?

Germany’s Dr. Norbert Hermanns’ blunt opening statement summarized nicely the current status of CGM reimbursement in his country – “The situation is VERY unsatisfying.” It was one of the more patient-centered attitudes we heard on the day, a sentiment that is not often associated with the Germany’s Federal Joint Committee (G-BA). As a reminder, the G-BA has been particularly challenging in diabetes where, on the drug front, it found no added benefit with Sanofi’s Lyxumia (lixisenatide) in 2013 (prompting the drug’s withdrawal) and in 2007 ruled that the benefit of then-Lilly’s Byetta (exenatide) was not yet proven. On the device side, the decision on CGM reimbursement has proceeded excruciatingly slowly (it started in 2011!) and it sounds like the timeline is still wide-open. For context, Dr. Hermanns shared that IQWiG (the country’s independent scientific institute that provides the G-BA with reimbursement recommendations) has acknowledged a benefit to CGM and sent its report to the agency in May 2015. At the same time, he pointed out that the data summarized by IQWiG is not the most convincing as it doesn’t incorporate results from the newest devices (no surprise considering this process has been going on for the greater part of five years!) and he did not sound particularly hopeful. Ultimately, we continue to find it tough to get a grasp on how German authorities are thinking about diabetes.

Dexcom CGM Beyond 2016

Jorge Valdes (CTO, Dexcom, San Diego, CA)

Dexcom CTO Jorge Valdes shared a few small pipeline updates: (i) the new G5 smaller transmitter (expected in late 2016 or early 2017, per JPM) will cut the volume in half vs. the current transmitter (previously, no size reduction estimate had ever been given); (ii) G5 Android is still expected to launch this year, though Dexcom won’t be able to cover every single Android phone – it will support the major brands, given the sheer number of Android phones; (iii) Dexcom will incorporate predictive hypoglycemia alerts into G6, offering a 15-minute prediction window – the design is balancing more advanced notice without increasing false alarms or annoying patients. The predictive alerts were the focus of many slides for the first time, which made us wonder if it was an answer to Medtronic’s hypoglycemia prediction app with IBM (which has a 2-4 hour prediction horizon, but could obviously increase alarm fatigue). The new predictive alert is clearly effective: with its addition, only 9% of 55 mg/dl BG events would give patients <15 minutes of warning vs. a much higher 42% with just a threshold alert alone. Overall, the new featurehas a 93% predictive hypoglycemia alert detection rate (for 93% of YSI readings <55 mg/dl, a predictive alert occurred between 0-30 minutes), but not at the cost of additional nuisance: for just 11% of predictive alerts, there was no YSI reading below 70 mg/dl within the next 30 minutes, making these alerts unnecessary). We’re glad to see Dexcom balancing valuable prediction with hassle factor – it doesn’t matter if an alarm is accurate if it is annoying!

Mr. Valdes mentioned several times that Dexcom’s G5 is accurate enough to dose insulin on (consistent with the EU label that it replaces fingersticks), though we noticed a slight step away from the longstanding emphasis to eliminate fingersticks – he mentioned that dosing insulin can be lethal, and Dexcom wants to keep calibrations in for safety. Was this an indirect comment to address Abbott’s factory calibrated FreeStyle Libre, which also has a dosing claim in Europe but requires no calibrations? It also might reflect expectations for G6 to include one fingerstick calibration per day. The final slide on “Dexcom’s R&D Mission” also excluded eliminating fingersticks (though we loved the clear goals):

In a follow-up conversation, management shared the following helpful perspective: “We are not backing off from eliminating fingersticks. But going forward we can see multiple classes of products, some requiring calibration and some not depending on the use case. We do believe that all sensors should allow calibrations, whether required or not, in order to cover the cases when the glucose reading do not align with the way a patient feels.”

T1D Exchange Data - The Largest Analysis Of CGM Use Informs The Future

David Price, MD (VP Medical Affairs, Dexcom, San Diego, CA)

Dr. David Price shared CGM data from the T1D Exchange, highlighting increasing adoption (now at 15%; total n=16,853) and a strong preference for Dexcom (63%) over Medtronic (27%). Nearly 80% of Dexcom users use CGM >25 days per month vs. ~45% of Medtronic users. The Exchange is not truly representative of the US type 1 population – its pump penetration is at 60% – though we think it provides an instructive look at what leading centers are doing. Dr. Price also discussed Exchange data comparing A1cs in MDI, pump, MDI+CGM, and MDI+pump, showing that in every age group, the same pattern holds – lower A1cs with CGM regardless of insulin delivery method (~0.6%-1.3% lower), and similar A1cs for CGM users on MDI or a pump. Dexcom has shown this in several exhibit halls, though we agree it is a compelling to counteract that prevailing belief that a CGM should come after a pump.

Use of The FreeStyle Libre System in Intensively Managed Adults with Type 2 Diabetes

Gerry Rayman, MD (Ipswich Hospital NHS Trust, UK)

Dr. Gerry Rayman presented case studies from Abbott’s six-month outcome study – REPLACE (n=210 type 2s on MDI, A1c>7.5%) – that will support reimbursement for FreeStyle Libre in type 2 patients. Dr. Rayman did not share specific findings or updates though we found it exciting nonetheless to get a sneak peak some glucose traces from a few patients. [We point out, of course, that these were likely carefully selected examples to demonstrate Libre’s efficacy.] As a reminder, the goal of the study was to show a change in A1c at six months (in patients with a high A1c >7.5%) and Dr. Rayman’s presentation focused on three “success” stories: (i) a patient (baseline A1c: 9.9%) who saw improved glycemic control at six months (A1c: 8.1%) with a non-significant change in hypoglycemia (0.84 hours/day [baseline] vs. 0.77 hours/day [six months]); (ii) a patient whose A1c remained stable (baseline: 8.6% vs. six months: 8.5%) but who saw significant improvement in hypoglycemia (1.65 hours/day [baseline] vs. 0.55 hours [six months]); and (iii) a patient who saw significant improvements in A1c and hypoglycemia – the “ideal” case. We can also imagine successful cases where A1c rose and hypoglycemia fell but nothing like this was shown. Full results from the trial will be presented Friday afternoon (see our preview).

Dr. Rayman shared a striking testament to Libre’s real-world accuracy, presenting SMBG data indicating that all three patients went from multiple fingersticks a day to “virtually none” once they started on Libre. The product label does recommend a confirmatory fingerstick when hypoglycemic, during times of rapid change, and when symptoms do not match reading, though we continue to hear that patients are pretty much eliminating fingersticks entirely. Abbott is presumably pursuing a similar insulin-dosing claim at the FDA though this has proven to be a regulatory conversation that has moved slowly (per 4Q15 commentary). Still, management optimistically expects FreeStyle Libre to launch by the end of 2016 in US.

First Clinical Experience with the FreeStyle Libre System in Young Adults and CHildren with Type 1 Diabetes

Fiona Campbell, MD (Leeds Teaching Hospitals Trust, UK)

Dr. Fiona Campbell discussed the challenges of successful diabetes management in young adults and children by putting the disappointing status of glycemic control in this population in context. She shared 2013 data from the T1D Exchange, indicating that a majority of pediatric and adolescent patients did not meet ADA or ISPAD guidelines for glycemic control (ADA: <8.5% for those younger than 6 years of age, <8.0% for those 6-13 years of age, and <7.5% for those 13-20 years of age; ISPAD: <7.5% for all ages. Dr. Campbell stressed that the numbers reflect the underutilization of CGM in this population, stating aptly that, “Parents and families LOVE it … but the kids not so much.” She noted, however, that diabetes self-management can be significantly improved when complete glycemic profiles are available, noting that FreeStyle Libre is uniquely positioned to provide such data given: (i) its 14-day wear time; (ii) its factory calibration (no fingersticks); and (iii) the lack of alarms. Within this framework, Dr. Campbell presented case studies from the pediatric accuracy trial (BEAGLE), demonstrating that FreeStyle Libre use can help identify patterns of hypoglycemia, post-prandial excursions, and elevated glucose variability. She did not present specific findings – these will be shown in a Friday oral and perhaps during a press conference Thursday – though her enthusiasm for Libre was telling. As a reminder, Libre is not yet indicated for use in the pediatric population though it sounds like many pediatric patients are already using the system off label in Europe. That said, it will be excellent for Abbott to get the official label as the clinical value of Libre in this younger population seems quite clear.

Clinical Use of the FreeStyle Libre System in Adults with Type 1 Diabetes

Emanuele Bosi, MD (Vita-Salute San Raffaele University, Milan, Italy)

Dr. Emanuele Bosi provided a very straightforward review of the clinical use of the FreeStyle Libre in patients with type 1 diabetes. Through a series of cases, Dr. Bosi documented improvements in glycemic control, risk of hypoglycemia, glucose variability, and quality of life that he has observed over the first ~1.5 years of Libre’s availability in the EU. He did not share specific updates or new data, though the simultaneous improvements in A1c and hypoglycemia in his cases certainly piqued our interest about what data from Abbott’s six-month reimbursement study in type 1s – IMPACT (n=225 type 1s on MDI or pumps, A1c <7.5%) – will look like at ADA 2016.

Digitalization and Automation in Personalized Diabetes Management

Matthias Axel Schweitzer, MD (Roche, Mannheim, Germany)

Roche’s Dr. Matthias Axel Schweitzer stated that the artificial pancreas is “clearly on our agenda.” In a talk on using technology to personalize diabetes management (that featured questions from our own CES report on the opening slide), Dr. Schweitzer indicated that more work needs to be done to perfect closed-loop algorithms, but that the company is “more than well prepared” for the future. We were very encouraged to hear this, as we have heard nothing from Roche on the closed loop in recent years. Dr. Schweitzer also commented that clinical studies of Roche’s novel CGM are going well and that the product will be available soon. This is consistent with the 2016 EU launch timeline Roche provided for the product – now being called the Accu-Chek Insight CGM – in its 4Q15 update. We are encouraged by Roche’s recent excitement around this device and hope to learn more about how the company plans to differentiate itself from its more seasoned competitors in this area. The remainder of Dr. Schweitzer’s talk focused on health apps (promising in theory but lacking hard evidence), the benefits of automated bolus calculators and carb estimators, and Roche’s efforts to address aspects of diabetes management beyond technology (such as with its Emminens automated pattern detection software for clinicians and a new behavioral training program for diabetes nurse educators).

3. Insulin Delivery

Digital Advisors For Patients And Caregivers

Tidepool: An Open Source, Extensible Platform For Diabetes Management And Research

Howard Look (President/CEO, Tidepool, Palo Alto, CA)

Tidepool’s Mr. Howard Look shared that the non-profit hopes to release its novel Nutshell app “within the next quarter,” enabling users to improve mealtime insulin dosing by keeping track of insulin and glycemic data from past meals. By logging and integrating mealtime data (bolus, correction, pre- and postprandial blood glucose values), Nutshell delivers insights that can help users make more informed bolusing decisions for future meals. We LOVE this, since patients tend to eat the same meals, and it makes perfect sense to look at what happened last time and make more informed decisions. Nutshell is currently in beta testing, and will be freely available via open source after its launch. This is the first we’ve heard on a specific launch timeline for Nutshell; we first wrote about the app in January 2014 and we are thrilled to hear that Tidepool is moving forward with it in the next few months. We do wonder about entry burden, since no Tidepool-compatible pumps can send bolus insulin levels in real-time to the phone; presumably those will be manually entered. We assume Dexcom data will important directly for G4 Share and G5 users. We were fans of Meal Memory when it launched, though it had some serious shortcomings we hope Nutshell will overcome: inability to search, no location-based notes, and more listed here.

Mr. Look also noted that Tidepool’s partnerships with Animas (Ping, Vibe) and OneTouch (VerioIQ, Ultra2, Ultra Mini) will be launching soon, building on compatibility with Dexcom, Insulet, Tandem, Abbott, and Bayer (Medtronic and Roche have still not officially authorized Tidepool to read data from their devices, though Tidepool can import data from Medtronic’s CareLink Personal). We have been continually impressed with Mr. Look and his team for their outstanding efforts in making diabetes data more accessible, more open, and more actionable, and we look forward to providing a deeper perspective on Nutshell when it launches.

Why Do We Need Advisors?

In a symposium on digital advisors, Dr. Moshe Phillip also presented on the general rationale behind MD-Logic Pump Advisor’s prescription therapy (“software as a drug”). Emphasizing the complexity of diabetes management and the shortage of endocrinologists, Dr. Phillip discussed the many challenges patients and physicians face (i.e., swamped with information, limited time and knowledge to perform optimization, etc.). He pointed to the promise of diabetes data management platforms (i.e., Diasend, Glooko), but noted that these systems do not suggest any solutions, highlighting the need for software prescription therapy. He briefly introduced the MD-Logic Pump Advisor and reviewed a few patient cases from a feasibility study – they showed less variability and fewer postprandial highs following pump settings optimization. We look forward to seeing even more data, as we really believe this could improve care; see the Glooko presentation for more on this exciting software.

Issues in Insulin Delivery

Use of Inhaled Regular Human Insulin in Type 1 and Type 2 Diabetes

Bruce Bode, MD (Atlanta Diabetes Associates, Atlanta, GA)

After reviewing the clinical data on Afrezza showing a fast-on, fast-off profile, some weight and hypoglycemia advantages vs. rapid-acting analogs, and no major safety concerns, Dr. Bruce Bode spoke quite positively about the enthusiasm the product has received from a select group of patients – “it changes their life.” He did note that using CGM may be necessary for many patients to do well on Afrezza. We heard similar comments from MannKind CEO Mr. Matthew Pfeffer at JP Morgan, where he noted that patients on CGM are better able to perform real-time titration of Afrezza and see its minute-to-minute effects on blood glucose. If true, this does not bode particularly well for widespread uptake of Afrezza given the small percentage of patients (especially those with type 2 diabetes) currently using CGM. Dr. Bode offered several potential explanations for Afrezza’s unexpectedly slow ramp-up (which led Sanofi to terminate its partnership with MannKind last month): lack of awareness, safety concerns, the spirometry testing requirement, lack of insurance coverage, high cost, use of subpar basal insulins, and the inability to promote hypoglycemia advantages. Our impression is that poor reimbursement has been the biggest obstacle to uptake, but the discussion during Q&A (see below) suggested that long-term lung safety may be a more salient concern for providers than we might have thought. Dr. Bode responded that he has not met any lung biologists with concerns about Afrezza and that because the drug does not remain in the lungs over time, there should be no risk of diseases like mesothelioma or silicosis that occur after decades of exposure. The FDA-mandated pulmonary safety study of Afrezza should help allay these concerns to some degree, though generalizability may be a question if it is conducted only in the highest-risk patients (long-term smokers). More immediately, MannKind faces a steep climb to turn Afrezza’s performance around before it runs out of cash – see our coverage of the company’s JP Morgan presentation and recent investor call for more on its strategy to do so.

Questions and Answers

Q: In other disorders involving particles in the lung, there’s a huge latency period measured in decades. With silicosis, minors have to be exposed for 30 years. With mesothelioma, you need 20-30 years of asbestos exposure. We don’t want to learn 30 years from now that pulmonary insulin produces the same thing. Cancer is not the only endpoint; there’s pulmonary hypertension, fibrosis, etc. With some of these lung disorders, there are animal models to concentrate the time constant and determine whether there’s this kind of effect. Are these studies being done to look at long-term exposure?

A: There’s been tremendous work by lung biologists. There is no residence of insulin over time in the lung. It comes back up with the cilia, people cough and swallow it – it doesn’t have any action. This has been done all the way in development from Pfizer to Novo to Lilly to MannKind. They’re not worried at all. They’ve done multiple bronchial lavages and tracers and seen no activity. With asbestosis and silicosis and tobacco, the substance hangs there. That’s not true for insulin. But the FDA still wants long-term studies, especially in people prone to lung cancer, to look at that. You have to understand that there’s no action of insulin in lung tissue, but we do want to do that.

Dr. Satish Garg (University of Colorado, Aurora, CO): Having practiced medicine for nearly four decades in type 1 diabetes, we’re dealing with enough morbidity in these patients. Why add another long-term effect the drug might cause in the lungs? The question is not only insulin as a growth factor but what will happen with something else present in the inhalers?

A: I can only share the comments I’ve heard from lung biologists, and they have no concerns. I have never met a lung biologist who had a concern. Obviously insulin is a growth factor, but is it correlated at all in subcutaneous fat with cancer? No. Fat is maybe not the best thing to look at, but in general there’s very little correlation of exogenous insulin with cancer – endogenous certainly is but that’s due to insulin resistance and probably other issues. The lung biologists are the experts; they spend their lives doing this. But you’re right, I agree with the FDA that they should do a long-term safety study, but there’s no signal there. DLCO [diffusion capacity of the lungs for carbon monoxide] was not significantly down. In certain trials it was but they say it was not significant in all of them. They did full pulmonary function tests in the development program.

It’s a moot point now because Pfizer pulled out not because of lung issues, but because they thought they could take over the whole market and you can’t launch something new and change behavior in a year. It takes at least five – if you look at the DCCT, it took seven to nine years to have people change their practice. Sanofi was hoping to see quick uptake but obviously it didn’t happen. I talked to Al Mann and he said they’re pricing it so high; you can do this for a dollar a day. There are so many people in poor control who don’t take insulin or they miss insulin or they have hypoglycemia. It’s his vision and I agree because there’s an unmet need. It’s big pharma that doesn’t want this. Rapid-acting insulin is a multi-billion-dollar industry.

Dr. Garg: We did a study seven years ago in this area. Because of the rapid uptake and decline with inhaled insulin, you don’t have a tail. We realized rapidly that’s important to overall glucose management. We clearly saw that unless you give five or six inhalations a day and two per meal, you will not get a drop in A1c. That’s why even though the non-inferiority trials were definitely met within 0.4%, when you look at it, it was really inferior by 0.2% vs. NovoLog.

A: I agree. They didn’t use longer-acting basals. If CGM was the standard of care and everyone used it, inhaled insulin would just take off. You can determine what you need to do. If you give inhaled insulin to a person who has never injected or who is struggling with injections, they love it. Most people won’t use it for the same reason you asked the question, about long term what happens 30 years from now. People smoke 20 cigarettes a day and the tar hangs in there. We don’t see that in tracers or any insulin activity.

Oral Presentations

Clinical Safety and Feasibility of the Advanced Bolus Calculator for Type 1 Diabetes Based on Case-Based Reasoning: A 6-Week Non-Randomized Single-Arm Pilot Study

Monika Reddy, MRCP (Imperial College London, UK)

Dr. Monika Reddy presented positive results from a six-week pilot study (n=10) of the ABC4D advanced bolus calculator system in type 1 diabetes. This advanced bolus calculator uses case-based reasoning, an artificial intelligence technique that solves newly encountered problems by applying solutions learned from solving similar problems encountered in past cases. The findings found that at six weeks, participants (baseline mean age of 42 years; 21 years of disease duration; A1c of 8%) experienced a reduction in hypoglycemia episodes and improvements in glycemic outcomes. Specifically, the number of hypo episodes within four post-prandial hours decreased from 3.5 to 1 over six weeks. The percentage of time spent in ranges under 2.8 mmol/l (52 mg/dl) decreased from 0.8% to 0.4% while the time percentage in the range of 3.9-10 mmol/l (70-180 mg/dl) increased from 55% to 61%. A qualitative evaluation of the findings also found that participants found the ABC4D user-friendly and trustworthy. In addition, Dr. Reddy pointed to the potential benefit of glucose rate-of-change as a valuable parameter for insulin dosing decision support, as results demonstrated that the minimum post-prandial glucose for meals where the glucose ROC was rising compared to stable levels was 158 vs. 115 mg/dl respectively. Moving forward, Dr. Reddy shared that her team has recently begun a six-month randomized controlled study of the ABC4D system, with 150 participants. We see lots of upside for improving mealtime insulin dosing, particularly adding CGM trends and historical bolus performance.

Mobile And Web Based Insulin Decision Support

Rick Altinger (CEO, Glooko, Palo Alto, CA)

Glooko CEO Rick Altinger shared the company’s exciting plans to develop two insulin decision support tools within Glooko: the DreaMed MD Logic pump advisor (funded with $3.4 million from HCT’s Diabetes Data Innovation Initiative) and a mobile insulin dosing system (MIDS) that makes it easier for people new to insulin to setup and manage titration calculations for type 2 diabetes. This was the first-ever mention of the latter, which could be very impactful in our view, particularly in the PCP setting. Both systems will help clinicians be more efficient and effective as the software will do analysis and give clinicians crystal clear decision support for changing insulin doses (e.g., for pump users, change basal from 0.95 u/hr -> 0.8 u/hr from 12-8am due to pattern of nighttime hypoglycemia; for MDIs, increase basal insulin dose by two units based on high morning fasting BG). With the DreaMed advisor solution, clinicians will then approve the recommendations (or edit them if desired) and transmit the data back to a patient’s Glooko mobile app. This seems like a reasonable, step-wise regulatory path, and as the algorithms are proven, patients and clinicians will hopefully receive the recommendations at the same time. Both systems are still in the pilot-testing phase, though no specific commercialization timing was discussed. Mr. Altinger said that in early tests, the DreaMed pump advisor has shown “very strong” results and made an “enormous impact.” We have long thought insulin titration is one of the biggest challenges in diabetes – particularly for overwhelmed PCPs – and we’re elated to see Glooko prioritizing tools to make it easier. We wonder how efficacious these products will be in clinical studies and real-world use; obviously, it only works if patients upload their data, if clinicians configure the system, and patients then act on the reminders received in their mobile phones. More broadly, Mr. Altinger emphasized Glooko’s focus on integrating with electronic medical records like EPIC – “In order to solve decision support, we have to integrate into the workflow with the big EHRs... In the US, EPIC manages 179 million patients.”We’re impressed to see how farGlooko has moved from a universal meter cable just a few years ago to a growing web and mobile diabetes data management platform.

Mr. Altinger provided the most detailed look yet at the DreaMed pump advisor – funded by the Helmsley Charitable Trust with $3.4 million to start the week – which recommends specific pump settings changes (basal rate, correction factor, and active insulin time) based on patients’ pump, CGM, exercise, and food data. Glooko will collect patient device data through its mobile and web-based system (supporting 40+ glucose meters, Dexcom CGM, Freestyle Libre, Insulet’s OmniPod, and soon Medtronic pumps and sensors). This data is de-identified and run through the DreaMed MD Logic Pump Advisor, which generates recommendations that are sent back to a clinician via Glooko’s web-based platform. Clinicians view and approve the recommendations (or edit them), and with a click, send them to the patient’s mobile device. Notably, Glooko will allow the recommendations to be fed into EHRs and fit into clinicians’ workflow (e.g., clinicians can elect to send the recommendations to patients through EPIC myChart messaging). The system will also give patients guidance on how to change their pump’s insulin settings – excellent!

Glooko’s mobile insulin dosing system (MIDS) for type 2 patients on long-acting insulin will help clinicians and patients continuously titrate insulin based on observed glucose readings (pictures below). A clinician will select and/or configure insulin-dosing titration instructions, with the option of selecting standard titration schemes (e.g., AACE geriatric dosing template). Clinicians enter a patient’s basic information, type of insulin, glucose range, and time periods. A patient’s mobile device then receives the personalized dosing configuration, with reminders to check glucose and to take insulin doses which are recalculated based on the clinicians configuration (e.g., “It’s checkup time! Let’s see if your insulin dose needs to be adjusted.”). The system also sends safety alerts (e.g., “We’ve detected you have a reading under 70 mg/dl. Contact your physician….”) Patients dose will change on a regular basis based on the glucose readings collected (the system showed Roche’s Bluetooth-enabled Accu-Chek Connect meter) and the clinician’s configuration of MIDS. Clinicians can monitor remotely, with everything integrated into EHRs.

Mr. Altinger applauded Sanofi’s new MyStar Dose Coach meter as a “good start,” but called it an “island solution.” As a reminder, this meter suggests insulin-dosing changes directly on a new meter supplied from Sanofi that a clinician would configure to one of three pre-configured insulin titration schemes (see our coverage from Wednesday). This meter only handles three specific insulin titration configurations, and would also require patients to change meters. That said, building the algorithm right into the meter is an appealing convenience solution.

Demonstration of Glycemic Control in Recent PAQ Clinical Study

Julia Mader, MD (CeQur, Marlborough, MA)

CeQur’s Dr. Julia Mader presented encouraging preliminary data from the company’s study of its insulin delivery device in patients with type 2 diabetes (n=15). Preliminary results indicated that PaQ treatment reduced A1c 1.5% from a baseline of 8.8% (p<0.0001). For context, the trial consisted of three study periods: baseline MDI (one week), transition from MDI to PaQ (1-2 weeks – to ensure that patients were on an appropriate basal rate), and PaQ treatment (12 weeks). Looking at individual data, it was great to see that every patient who transitioned to PaQ experienced an A1c reduction (i.e., 100% of patients saw some glycemic benefit) and given the short duration of the study, we would note that the 1.5% A1c reduction is very impressive. Secondary outcomes were also encouraging as total daily dose of insulin (TDD) and body weight were not statistically different from baseline – both metrics technically hinted at a slight increase though Dr. Mader attributed this trend to an artifact of the small sample. On the insulin dose front, 73% of patients successfully transitioned to PaQ with the first basal dose, which we hope is a good sign that HCPs will have an easy time transitioning patients onto PaQ. No severe hypoglycemic events or other serious adverse events were reported.

4. Additional Topics

Plenary

Yearbook

Day #3 of the meeting featured the celebrated ATTD Yearbook sessions – check out the publication online here. The comprehensive plenary reviewed the year’s progress in: (i) self-monitoring of blood glucose; (ii) new medications for the treatment of diabetes; (iii) continuous glucose monitoring; (iv) insulin pumps; (v) closing the loop; (vi) new insulins, biosimilars, and insulin therapy; (vii) using digital health technology to prevent and treat diabetes; (viii) immune intervention in type 1 diabetes; (ix) advances in exercise, physical activity, and diabetes mellitus; (x) diabetes technology and therapy in the pediatric age group; and (xi) diabetes technology and the human factor. The online publication is recommended reading for a literature year-in-review!

Plenary: Opening Ceremony

Glucose Variability: A New Challenge in Diabetes Management

Antonio Ceriello, MD (University of Udine, Italy)

During the opening ceremony, Dr. Antonio Ceriello argued that glucose fluctuations cause greater oxidative stress and present an increased risk of complications relative to stable high glucose levels. To that end, he shared new unpublished data from his team’s study comparing the effects of constant versus intermittent high glucose levels on antioxidant enzyme expression in human endothelial cells. The results demonstrated that intermittent high glucose levels were associated with significantly lower levels of antioxidant GPx1 than constant high glucose levels, leading to increased cellular damage by free radicals. Dr. Ceriello presented additional corroborating data from a series of studies stretching back to the early 2000s, highlighting the fact that greater glucose variability has been largely associated with higher risk of complications (we’re working to get details since we have never seen this exactly – we’ve seen poor interpretations of DCCT claiming to disprove this), and emphasized the importance of creating a standard for measuring glycemic variability (which is typically measured using standard deviation or mean amplitude of glycemic excursions [MAGE]). We see this as particularly valuable as therapies and technologies develop that improve time-in-range by reducing hypoglycemia at the (theoretical) expense of A1c. Dr. Ceriello was emphatic that well-designed clinical trials are sorely needed in the field but acknowledged that they are difficult to perform (and fund, we would add). He commented on the ongoing FLAT-SUGAR trial as an example, expressing concern that the study may not be successful long-term due to the complexity of glucose variability and its dependence on a broad range of uncontrollable factors such as blood pressure and cholesterol levels. (As a reminder, what was somewhat unclear from the preliminary FLAT-SUGAR results was whether the magnitude of glycemic variability reductions would be large enough to show long term differences in future outcomes.) We wouldn’t be so quick to dismiss the future potential of FLAT-SUGAR as there are still plenty of analyses to do on these data. It’s entirely possible different perspectives on variability will emerge over time and are hopeful we will learn more on Saturday afternoon when the brilliant Dr. Irl Hirsch is slated to present the next iteration of FLAT-SUGAR results.

Oral Presentations

Brett Newswanger (Xeris, Austin, TX)

Xeris’ Mr. Brett Newswanger presented results from a human factors study showing significantly greater success rates with the company’s G-Pen glucagon auto-injector vs. currently marketed glucagon kits (from both Lilly and Novo Nordisk) in a simulated episode of severe hypoglycemia. The study enrolled 16 participants, including eight caregivers/emergency personnel who were familiar with current glucagon kits and eight who had no experience with glucagon. Half the participants received training at the beginning of the study (on both glucagon kits for the naïve participants and only on the G-Pen for the experienced participants) and half did not. All participants performed one unaided rescue injection with each product in a randomized order. 88% of participants (14/16) successfully administered a rescue injection with the G-Pen compared to only 31% (5/16) with the current kits. In addition, the mean total rescue time (from entry into the room until delivery of the dose) was 35 seconds with the G-Pen vs. 96 seconds with the current kits – as Mr. Newswanger noted, this is a huge difference in an emergency situation. There was no difference in the success rate between experienced and naïve participants. Not surprisingly, all participants stated that they preferred the auto-injector over the current rescue kits. Comments included “Super easy and super safe!” and “When can I take this home?” Of the two people who failed to successfully administer glucagon with the auto-injector, one did not remove the cap on the device and the other attempted to inject through clothing. In part because of these errors, Xeris has changed its secondary container from a cigar tube to a pouch (so there is only one cap to open) and placed instructions directly on the pouch so they are more visible.

Investigators aimed to simulate a real hypoglycemic emergency as closely as possible. Participants entered a room with a fully clothed manikin at the center and were told that the “patient” was in urgent need of medicine. The investigators even projected noise into the room through speakers to simulate a restaurant setting. However, unlike in a similar study of Locemia’s (now Lilly’s) intranasal glucagon presented at EASD, the pouch next to the manikin contained only glucagon, not insulin. While certainly not required, we thought the inclusion of insulin in the Locemia study was a nice touch that illustrated the potential for confusion between two injected drugs in an emergency (two participants in the control group attempted to inject insulin instead of glucagon).

Xeris will initiate phase 3 trials for the G-Pen “shortly.” The company expected to begin phase 3 by the end of 1Q16 as of early January, when it announced the closing of $41 million in Series C financing to accelerate development. This timeline is behind Xeris’ previous goals to begin the study by the end of 2015 or even earlier. Xeris also has two chronic glucagon programs in phase 2 that we have not seen data on in some time: G-Pen Mini (a glucagon pen for mild and moderate hypoglycemia) and G-Pump (pumpable glucagon for the bi-hormonal closed loop).

Lilly’s intranasal glucagon (acquired from Locemia) will likely be the G-Pen’s most direct competitor. Lilly will likely be first to market with a next-generation glucagon, having already completed phase 3 trials, and its vast experience in diabetes and specifically in glucagon should provide important advantages. It is an open question whether more patients and caregivers will prefer an intranasal device compared to an auto-injector – a human factors study comparing the two would be fascinating. Zealand and Sanofi (as of its 4Q15 update) both have stable glucagon candidates in phase 1. Biodel was a contender in this race until recently, but it indefinitely suspended development of its Glucagon Emergency Management auto-reconstitution device in December due to contract disputes with manufacturing partner Unilife.

Questions and Answers

Q: Can you change the dose for small children?

A: We’re making two products: a 1 mg dose and a 0.5 mg dose. You can buy the 0.5 mg version for pediatric patients.

Q: Is it available now?

A: No, we’re doing phase 3 shortly this year

Q: Is the duration of action of this type of glucagon the same as the other products?

A: Correct. It’s the same molecule. It’s a synthetic peptide but the same peptide sequence. Our technology is a formulation of the peptide.

Highlights Toward 2016

FLAT-SUGAR

Irl Hirsch, MD (University of Washington, Seattle, WA)

Dr. Irl Hirsch summarized the results from the FLAT-SUGAR study (presented at ADA 2015), conveying interest in repeating the trial in type 1. He is talking to potential funders, though confirmed with us later that these discussions are not yet type 1 specific. He again characterized the 26-week, 102-patient feasibility trial as successful, showing it is possible to randomize ACCORD-like type 2 patients to two groups (exenatide+glargine+metformin vs. rapid-acting insulin+glargine+metformin) and achieve significantly different glycemic variability (coefficient of variation) with a similar A1c (7.1% vs. 7.2% in this case). However, he acknowledged some of the questions we posed at the time: Are the differences in variability and hypoglycemia large enough to support a modern DCCT comparing high and low glycemic variability with the same A1c? Should the study have been done in type 1? Dr. Hirsch said that when the trial was being planned in 2010-2011, doing it in type 1 would have been unethical; in Q&A, however, he wondered if it could now be repeated comparing MDI + SMBG vs. an artificial pancreas – exciting indeed, and a design that should clearly show large differences in variability. Dr. Hirsch said the team is talking to “potential funders” (not type 1 specific), and our fingers are crossed this could actually be done. Regarding the low rates of hypoglycemia in insulin-using type 2s, Dr. Hirsch commented that the study picked top-notch investigators (Joslin, IDC, UNC), which helped the insulin group do very well. He quickly showed new data on arrhythmias, though there was no difference between the two groups (they avoided hypoglycemia too well). Dr. Hirsch emphasized the trial’s highly complex design, lengthy recruitment, and lessons learned, and was optimistic that it has still forced clinicians to think beyond A1c. We hope that more analyses and a future potential study in type 1 further reflect that takeaway. ATTD 2016 again reminded us of A1c’s limitations (e.g., Abbott’s REPLACE data), and we hope a trial can definitively prove the long-term value of reducing glycemic variability independent of mean glucose.

Questions and Answers

Dr. Lori Laffel: Were there any side effects of exenatide?

A: It was surprisingly very limited. A minimal percent – much less than we saw in other trials with GLP-1.

Adam Brown (Close Concerns, San Francisco, CA): So what’s next? Do you try to redo the study in type 1? Do you go for the big outcomes study?

A: We are talking to potential funders now. I’m very interested in doing this study in type 1. Could that be MDI + SMBG vs. artificial pancreas? That would certainly be ethical. But I don’t know. We’re talking now.

Biosimilar Insulin

What Should The Prescriber Know About Biosimilars?

Dr. Philip Home provided a comprehensive take on what prescribers should know about biosimilar insulins, focusing mainly on the limitations of the available data. He noted that prescribers do not have access to the majority of the preclinical, manufacturing, and chemical characterization data on biosimilars and suggested that most would not have the skills to interpret it even if they did. He placed the responsibility on regulatory authorities and organizers of continuing medical education programs to help disseminate this information in an understandable way. He also suggested that many providers will likely rely on the manufacturer’s reputation as a proxy for manufacturing quality, which we imagine should work to Lilly/BI’s advantage in the case of biosimilar insulin glargine. On the clinical side, Dr. Home critiqued several aspects of the typical studies used to support approval. For PK/PD studies, he argued that endpoints like area under the curve and max concentration are not sensitive enough when comparing insulin profiles and that the typical confidence intervals are too wide in a case where a dose difference of 5% is clinically significant. In phase 3 trials, Dr. Home believes change in fasting or postprandial plasma glucose is a much more sensitive and clinically relevant endpoint than change in A1c – the need to move away from an A1c-centric view of diabetes has certainly been a recurring theme this week. He also suggested than hypoglycemia, while “usually ignored in this context by regulators,” is more important to patients and providers than the typical efficacy endpoints. Furthermore, in his view, adverse event-related endpoints cannot be adequately evaluated with current studies, as most trials are too small and too short, while post-marketing surveillance is too weak.

Insulin Access in the Developing World

Mr. Joseph Saldanha spoke about the potential for biosimilars to increase access to insulin in the developing world. He opened with some striking statistics about the current state of the insulin market: three of the world’s 42 insulin manufacturers account for 93% of the revenue and 92% of the production. The plan is that the advent of biosimilars will introduce more competition into this market, thereby lowering prices and improving access, which we were glad to hear is already trending in the right direction. However, Dr. Saldanha acknowledged that the prospect of investing ~$400 million to develop and manufacture a drug that is unlikely to provide a huge short-term return is a daunting one for many companies. Interestingly, he also suggested that discounts for biosimilar insulins are unlikely to be greater than 30%, partly because some physicians have indicated that they would not trust the safety of a cheaper product. This was an interesting new perspective to us, as we have assumed the more common reaction will be disappointment that biosimilars are not discounted on the same level as small molecule generics. The diabetes market research firm dQ&A has done extensive work on this front – if you are curious to know about the reaction of patients and providers, be in touch with the great Richard Wood at richard.wood@d-qa.com.

Changing The Natural History Of Diabetes

Developing Disease Modifying Therapies In Children With Type 1 Diabetes

Desmond Schatz, MD (University of Florida, Gainesville, FL)

Incoming ADA President Dr. Desmond Schatz delivered a passionate talk on the need for changes to the current paradigm for type 1 diabetes cure research. Much of his talk focused on the profound differences in the disease between children and adults: younger patients start out with less C-peptide at baseline, lose beta cell function faster, and often respond differently to therapies in clinical trials compared to adults. An excellent Consensus Conference on this topic last year covered these issues in great detail, and we hope this discussion can lead to changes in research and regulatory frameworks. Dr. Schatz also focused on the need to stage and develop treatments for early, asymptomatic stages of type 1 diabetes. This was the subject of a JDRF workshop in October 2014, which led to a new proposed classification system recently published in Diabetes Care. The framework divides type 1 diabetes into three stages: (i) multiple autoantibodies and normoglycemia; (ii) multiple autoantibodies and dysglycemia; and (iii) symptomatic disease. Dr. Schatz (and many others) hopes that this new framework can enable early clinical trials with intermediate endpoints to replace the “expensive and unwieldy” studies of the past. He pointed to TrialNet’s Abatacept Prevention Study as one promising example; the study has development of abnormal glucose tolerance as its primary endpoint and is slated to last four years (about half the duration of other recent prevention trials).

Dr. Schatz was adamant that combination therapy is the future of type 1 diabetes treatment. He urged those in the field to think outside the box, learn from other disease areas (AIDS, cancer, tuberculosis) in which combination therapy is the norm, and move away from searching for a one-time silver bullet. We have heard similar sentiments from a number of type 1 diabetes researchers, though one challenge noted by Dr. Jeffrey Bluestone (UCSF, San Francisco, CA) is that it is difficult from a regulatory perspective to conduct efficacy trials of combinations with no FDA-approved drugs – he believes achieving the first “foundational” approval will be an important step toward studies of more innovative combinations.

Various Settings for Management of Diabetes

Reading and Misreading the Evidence-Base for Diabetes Technology

John Pickup, MD (King’s College London School of Medicine, UK)

The esteemed Dr. John Pickup discussed several reasons for why much of the “best evidence” in the diabetes technology field is misrepresented or distorted, cautioning that while meta-analysis of randomized clinical trials is the gold standard, “all that is gold does not glitter”. We certainly agree with this. To that end, he asserted that short duration trials (<four to six months) and trials with first generation or outdated devices should not be included in meta-analyses as they are irrelevant and skew results – this was great to hear. In terms of study design, Dr. Pickup explained that exclusion criteria can lead to the selection of patients with no clinical problems, creating a misleading “no effect” outcome for a given intervention. For example, if patients in a pump study are well controlled at baseline and severe hypoglycemia is excluded at entry, then switching to CSII or CGM or closed-loop may show little to no effect in improving A1c. He stated that such misleading “no effect” outcomes also occur when trial participants have a response that is not measured in the study (e.g., A1c is measured but hypoglycemia is not). Dr. Pickup further explained that the convention of using mean values in data analysis is clinically “meaningless”; doctors treat patients, not means, and patient responses vary widely. Last, Dr. Pickup described his recent work checking the validity of published data in 11 RCTs using individual patient data. The results were alarming – many of the papers evaluated had major discrepancies (results entered in the wrong table columns, incorrect table legends, improver citations, etc.), and errors were not detected by the multiple authors, reviewers, and journal editors before submission – we are not too surprised with the latter since so many people in this field are being asked to do so much. Dr. Pickup concluded by advocating for stakeholders to collaborate in setting, regulating, and interpreting the diabetes technology evidence-base, highlighting the importance of establishing robust evidence to form the basis of clinical conclusions and healthcare policy. We agree that the value of strong evidence cannot be understated in diabetes technology – evidence determines regulatory approval, recommended usage in guidelines, cost-effectiveness, reimbursement policy, and patient outcomes, and is essential for positive progress in the field. And the bar is higher and more important than ever.

Preventing Readmissions in High Risk Diabetes Patients: Planning and Implementing a Transitional Care Program

Jane Seley, DNP (Weill Cornell, New York, NY)

Dr. Jane Seley shared the design and preliminary data of a new ongoing trial that aims to examine strategies on preventing hospital readmission in high-risk diabetes patients. Regarding key factors of readmission, she pointed to low socioeconomic status, racial/ethnic minority, multiple co-morbidities, public insurance, urgent admission, and recent hospitalization. In her study (n=36), Dr. Seley provides every patient with the opportunity to receive diabetes education, which includes three key strategies (in addition to the usual care of inpatient self-management education) as part of a transitional care flow chart: (i) “Med-to-Bed” medication delivery (patients have all prescriptions filled upon returning home); (ii) a three-day follow-up phone call; and (iii) a seven-day post discharge outpatient visit. According to the preliminary data, of the 36 participants, 11 participated in none of the strategies; five participated in all strategies; 14 participated in only “Med-to-Bed”; five participated in “Med-to-Bed” and the three-day call; and one participated in “Med-to-Bed” and the seven-day follow-up. We look forward to hearing more of Dr. Seeley’s findings, especially her insights on how to motivate and engage patients to participate in diabetes education, as such use appears to remain extremely low in even the most well-resourced patients – see our coverage of CDC data on this for more.

Surgical Solutions for Diabetes

Primoz Kotnik, MD, PhD (University of Ljubljana, Slovenia)

Dr. Primoz Kotnik presented new data, demonstrating that GI Dynamics’ EndoBarrier (endoscopic duodenal jejunal bypass liner) is a feasible therapeutic option for adolescents with severe obesity. The study included 15 participants, whose mean age was 17 years and mean BMI was 42 kg/m2. The results found that the majority of participants achieved meaningful weight loss, with a mean weight loss of ~16% and BMI reduction of 6 kg/m2 at 12 months. In addition, the findings demonstrated improvements in several metabolic parameters, including glucose metabolism, dyslipidemia, and blood pressure. According to a psychological evaluation at 12 months, participants also experienced some positive changes in eating behavior and other psychosocial measures (i.e. less socially withdrawn, physically aggressive). Results also demonstrated an acceptable safety profile within this patient population. As bariatric surgery remains relatively controversial in this age range, this data is promising in potentially expanding the number of treatment options for adolescents with severe obesity.

In addition, Dr. Kotnik briefly pointed to the liver abscess safety signal in the terminated US ENDO Trial, noting that the liver abscess rate elsewhere has remained much lower. Similar to the German Diabetes Society’s recent statement on the trial termination, he shared that the liver abscess rates globally (n=3,000) and in Germany (n=651) are 0.73% and 0.46%, respectively, compared to the US trial’s 3.2%. Regarding possible reasons as to why the trial’s rate is significantly higher, Dr. Kotnik pointed to the possible roles of the trial’s high-dose proton pump inhibitors, type 2 diabetes population, or even a difference in immune status. As a reminder, GI Dynamics reported in its 3Q15 update that the company has an ongoing review of the trial’s preliminary results – we look forward to this full data to gain a more comprehensive understanding of the device’s risk-benefit profile.

5. Exhibit Hall

Abbott

Abbott reps informed us that the company is “coming along” in the process of developing an Apple LibreLink app for scanning FreeStyle Libre sensors without the need for a separate reader. The timeline is not yet clear but we did learn interesting details about what the platform expansion might entail – the company is thinking about building an iPhone adapter to power the NFC-reading capability. As a reminder, the iPhone franchise (up to and including iPhone 5S) has not had NFC built-in and it sounds like this solution would work for both existing iPhones and the upcoming iPhone 6 (that, in fact, does support NFC but – according to the rep – does not have the ability to read data from Libre.) As we understand it, the adapter would be plugged into the headphone jack, would scan data from the sensor, and would then send the data straight to the app. We certainly applaud management for identifying a workaround though it does sound like a less-than-deal solution – requiring an adapter certainly negates the seamlessness and patient convenience of scanning with just a phone alone. We’ve long wondered if Abbott would develop a Bluetooth-enabled FreeStyle Libre sensor, though there are obviously serious manufacturing tradeoffs to doing so. The mobile experience is of course critical when thinking about staying competitive with Dexcom’s G5 and Medtronic’s Guardian Mobile.

Ascensia

Ascensia Diabetes Care made its first public appearance as a stand-alone company though aside from the new branding it does not appear that much has changed. The BGM line is now being marketed under “Contour diabetes solutions” and as one rep put it, “The people are the same. The products are the same. The only thing that’s different is what we’re called.” Reps did allude to a new Bluetooth-connected BGM in the pipeline that is slated to launch later this year; they did not provide specifics though it’s great to see Ascensia is on course R&D-wise.

CeQur

Exhibit hall reps shared that the company has delayed EU commercialization until after the US launch (previous guidance put the EU launch first, in 2016). We are not sure what is responsible for the about-face though it sounds like the decision will enable CeQur to scale up manufacturing and seek out US reimbursement without the presumable distractions of commercialization in the price-sensitive EU market. Reading between the lines, we wonder whether the latter was proving especially difficult in the EU, given both that there is no predicate device [Valeritas’ V-go is covered by third parties only in the US and reimbursement is way more of a hassle than it should be given the major benefits it has shown in terms of A1c and adherence] and that the team still has limited clinical data. CeQur did recently complete its third small pilot study (see the data below) and while the findings have been very encouraging (improvements in A1c have been >1.5% across the board), it is may take much larger observational studies and RCTs of glycemic impact and cost-effectiveness vs. MDI to appeal to payers. On the US launch, we also learned that PaQ will be indicated for “diabetes” broadly, not specifically for type 1 or type 2; of course, it’s been marketed toward the latter though we think the labeling choice is smart considering many patients with type 1 could find the simple device convenient and easy to use, especially those transitioning from MDI to pump therapy. Fortunately, CeQur does have funds to work with – considering the impressive $100 million in Series C financing the company raised last September – though we imagine it’ll take much of that to fund clinical operations and a launch.

Dexcom

“Dose with Dexcom” was the theme of Dexcom’s G5-focused booth, marketing the company’s insulin-dosing claim in Europe (first shared at EASD 2015) – that has a very cool ring to it, doesn’t it! Posters advertised the peace-of-mind remote monitoring advantages of G5 coupled with Share, something neither Abbott nor Medtronic has available in Europe (LibreLink does not have remote monitoring to our knowledge, and MiniMed Connect is only available in the US).

DreamMed

We had a chance to speak to DreaMed in the exhibit hall, where we confirmed the MD-Logic Pump Advisor’s design and learned of plans to begin the preliminary study this fall. The algorithm’s output is designed exactly as we had hoped – pattern recognition that identifies very clear, specific changes in pump settings like basal rates and insulin-to-carb ratio (e.g., change basal from 0.95 u/hr -> 0.8 u/hr from 12-8am due to pattern of nighttime hypoglycemia). We confirmed that the initial version will send patient data from the Glooko app to the physician, who will approve the MD Logic Pump Advisor recommendations and send it back to patients. The hope is to eventually the pump settings recommendations directly to patients without HCP confirmation. The team shared with us that it hopes to start the study this fall. As we noted on the first day of ATTD, the Helmsley Charitable Trust awarded $3.4 million to DreaMed to fund the Pump Advisor’s development (leveraging data from the Glooko platform).

Medtronic

In an exhibit hall surprise, Medtronic publicly displayed Guardian Connect, its standalone, Bluetooth-enabled mobile CGM targeted at patients not on pumps. Signs indicated it is currently under CE Mark review, which presumably means an EU launch could occur sometime later this year or early next year (our speculation, as reps would not comment on launch timing). The transmitter is the familiar clamshell design, though it will send CGM data via Bluetooth directly to a mobile app on Apple iOS at launch. Medtronic does not plan to launch a standalone receiver, so patients will only get the transmitter and app (unlike G5, where they have the option of using a receiver or the app). Interface-wise, Guardian Connect looks similar to the MiniMed Connect app, while retaining the text messaging notifications for caregivers and auto-upload to CareLink. We didn’t get to do a hands-on demo, but the app had the familiar glucose value, trend, and trace on the home screen, plus the obvious sub-menus for calibration and settings (see picture below). We see this as a key competitive answer to Dexcom’s G5 and Abbott’s LibreLink, plus an important Medtronic foray into MDI (Medtronic’s current real-time CGM requires a paired pump). Though we have known about this device sinceSeptember 2014 (pivotal study completed in August 2015), this is the first time it has ever been on display in final commercial form in an exhibit hall. As of JPM last month, Medtronic expected a US launch of Guardian Connect with Enlite 3 by April 31, 2017 (in FY17); there was no EU timing listed on the slide, which is what made this announcement very unexpected. We’re elated to the sensor field moving incredibly rapidly to make systems more convenient to use – who would have thought two years ago that we’d have all three players with smartphone apps to view data?!

Sanofi

Sanofi debuted its first-in-class MyStar DoseCoach in its exhibit hall booth – the device integrates an insulin glargine dose titration algorithm and BGM, providing guidance on insulin dose adjustments for patients with type 2 diabetes. According to sales reps, the device received a CE mark this past December, and this ATTD display is its first exhibit hall promotion. We assume it could conceivably launch soon in Europe; unfortunately, there is no US timing. The MyStar DoseCoach comes with three treatment plans based on “well-accepted titration algorithms” – these are entered into key cards that can be inserted and activated into the device by healthcare professionals (the plans differ on aggressiveness and target range). After selecting the most appropriate treatment plan for the patient, the healthcare professional can then individualize the Dose Helper by entering the patient’s weight, starting dose, and usual dose time. The patient then uses the device like a normal BGM to measure fasting blood glucose levels and to record insulin doses; after the patient runs Dose Helper, the device suggests an updated insulin glargine dose based on the selected treatment plan. Notably, the device is currently only available with Sanofi’s Toujeo (insulin glargine U300) for type 2 diabetes – in our conversations with reps, the company first wants to see how this device will fare on a smaller scale prior to any considerations for expansion. We have expected Sanofi and its MyStar initiative (read more about the initiative from its launch at ATTD 2013) to launch such a device for quite some time and we are very excited to see this new class of devices take flight. We hope this system’s convenience and more individualized insulin guidance will bring more patients to goal and save HCPs time.

We also like that the MyStar DoseCoach prioritizes safety, with multiple built-in verification and human factors rules. For example, prior to a fasting blood glucose measurement, the device confirms with the patient that the blood glucose measurement is indeed a fasting one, even going so far to help define what a “fasting” definition entails. While such notifications can be annoying, accuracy is critical when systems like this are giving insulin-dosing advice. The tradeoff is worth it!

MyStar DoseCoach downloads to MyStar Connect, a management software platform that collects all of the patient’s MyStar Dose Coach data (i.e., graphs and logbook) along with other health records in one spot for healthcare professionals. This data unfortunately cannot be synced in real time as there are no cloud connections (it must be manually connected during a doctor’s visit). We wonder what the plans are to integrate with Diasend, Glooko, and Tidepool, as well as how this product could fit within the Verily (Google Life Sciences) partnership.

Senseonics

The implantable CGM company had a full-fledged booth, showing off Eversense: its 90-day implantable sensor (complete with implantation demos!), body-worn transmitter, and mobile app. Eversense is still pending a CE Mark, and the plan is still to launch in the first half of this year in Europe (consistent with our January update on the company when it filed to go public on the NYSE). The sensor implantation procedure took five minutes, and the demo made it seem pretty easy (one incision and then inserting the sensor under the skin with a placement device). While we’ve long characterized the on-body transmitter as a drawback to the implantable system, it was smaller than we expected in person. Still, we were reminded that the transmitter is not waterproof in the first gen version, which adds daily hassle for patients (who must take the transmitter and adhesive off when showering and then reapply them) – to what extent that is a deal breaker for Eversense remains to be seen – how the device is presented will be very important. A brief demo of the Senseonics mobile app revealed the expected home screen layout (glucose value, trend arrow, trace), though Senseonics has chosen to shade the area under the trace – this makes the screen look more crowded in our view without much additional benefit. Separate from the booth, Senseonics announced an agreement with diasend to enable downloading of the Eversense system, an encouraging sign as it seeks to meaningfully commercialize this product. We hope this unique system can grow the underpenetrated CGM market – assuming pricing is competitive – and are glad to see the company pressing forward in a very competitive continuous glucose sensor market.

Unomedical

In a rare pipeline update, infusion set juggernaut Unomedical disclosed plans to launch a new all-in-one infusion set-insertion device in 2016. The single-touch, fully automatic serter will completely hide the insertion needle and retract it, and the whole unit will automatically detach from the inserted site. It’s an especially great innovation for those afraid of needles, those with poor dexterity, or those who have trouble inserting sites in difficult to reach places. We also like that it is full disposable and self-contained, adding a lot of all-in-one convenience for patients. Presumably it could improve the consistency of infusion site insertion, potentially even reducing site trauma. A poster in the booth also highlighted some earlier stage research at Unomedical: increased infusion set longevity (suppressing the inflammatory response at the insertion site, preventing cannula encrustation) and ensuring healthier skin throughout wear time (skin-friendly adhesive patches). There was no timing attached to these efforts, and a rep confirmed they are in the basic research phase. After years of little innovation in infusion sets, we are elated to see two new meaningful products coming to market this year – BD/Medtronic’s FlowSmart set and now Unomedical’s new automatic inserter! We expect these products to make pumping better for patients already on them, though we wonder about their long-term potential – can better infusion sets significantly enhance the clinical benefits of pumps, pushing more HCPs to prescribe them and more payers to encourage them?